I wrote many years ago that I felt physicists and photonics scientists were like Spock on Star Trek and that optical engineers were like Scotty. Spock would always understand the physics behind the problems and would usually save the day through some ground-breaking discovery that, on earth, would win the Nobel Prize. Scotty, in the meantime, would use what Spock had discovered to kluge together an effective way to power or protect the ship.

Ladar is becoming more prominent due to the maturation of its component technologies, especially lasers. There are many forms of ladar. There is simple two-dimensional (2-D) ladar, similar to a passive electro-optic sensor, but with controlled illumination and the ability to see at night even at short wavelengths. There is three-dimensional (3-D) ladar, with angle/angle/range information. 3-D images are very powerful because shape is an invariant. 3-D images can be easily rotated to various perspectives. You can add gray scale or color, just like passive, or 2-D ladar, imaging. You can add precise velocity measurement, including vibrations. Ladar generates orders of magnitude higher frequency change then microwave radar for velocity measurement, because frequency change is proportional to one over the wavelength. Orders of magnitude higher frequency change means you can measure a given velocity orders of magnitude quicker, in many cases making an accurate measurement possible. Polarization can be used. With an active sensor you control both the illumination and the reception, so you can pattern the illumination. Also, because ladar can use narrow band illumination it is easier to easier to coherently combine sub-aperture images to obtain the higher resolution of an array.

Abstract unavailable.

We present simple illumination devices with built-in speckle reduction using the spatial diversity approach. These devices are based on a waveguide homogenization technique with a transmission efficiency of up to 95%. Even for single-laser pulse illumination from a solid-state laser source a reduction of the speckle contrast by a factor of 4.5 was demonstrated. In detail, we present two different illumination devices based on either a solid-state laser source or an array of semiconductor laser diodes. These illumination devices are used for range-gated imaging and active polarimetry with speckle-free and homogeneous illumination.

We investigate range-gated imaging in scattering environments. Experiments were carried out in a fog chamber with different fog densities using a range-gated imaging system based on 532-nm laser illumination and an intensified charge-coupled device camera. The laser pulse width and the sensor exposure time were in the range of 500 ps. For the analysis of the impact of scattering environment on the depth resolution capability of the imaging systems, the Lissajous eye pattern method was applied. These analyses gave experimental evidence of the reduction of depth accuracy in the presence of scattering media. Further, the experimental data were compared to three-dimensional reconstruction using the least-square curve-fitting method.

Fast and reliable three-dimensional (3-D) measurement of large stack yards is an important job in bulk load-and-unload operations and logistics management. Traditional noncontacting methods, such as LiDAR and photogrammetry, witness difficulties of complex and irregular shape, single texture and weak reflectivity, and so on. In this paper, we propose a videogrammetry and projected-contour scanning method. The surface of a stack yard can be scanned easily by a laser-line projector, and its 3-D shape can be reconstructed automatically by stereo cameras. There are two main technical contributions of this method: 1. corresponding-point matching in stereo imagery based on image gradient and epipolar line; and 2. single projected-contour extraction under constraint of homography and RANSAC (random sampling consensus). The proposed method has been tested by 3-D-reconstruction experiments of sand tables in indoor and outdoor conditions, which showed that about five contours were reconstructed per second on average, and moving-distance error of a standard slab was less than 0.4 mm in the worst direction of the videogrammetric system. In conclusion, the proposed method is effective for 3-D shape measurement of stack yards in a fast, reliable and accurate way.

Three-dimensional (3-D) flash light detection and ranging (LADAR) imaging is based on time of flight (TOF) measurement of a single laser pulse. The laser pulse coming back from the observed object will be detected only if the number of photons received by each pixel generates a signal greater than the pixel noise. In order to extract this weak photonic signal from the noise we use the high gain and low excess noise of the HgCdTe avalanche photodiode (APD) arrays developed at CEA/LETI. The sensor consists of a 30-μm pitch APD detector array hybridized to a 320×256  pixels ROIC for passive and active imaging. In passive mode the focal plane array behaves like a thermal imager and we measured 30 mK of noise-equivalent temperature difference. In active imaging mode, each pixel sensed the time of flight and the intensity two-dimensional (2-D) of a single laser pulse. Laboratory tests show a range noise of 11 cm for 4300 photoelectrons per pixel and detection limit under 100 photoelectrons. The sensor was also used during a field trial to record 2-D and 3-D real-time videos. The quality of the images obtained demonstrates the maturity of HgCdTe-APD-array technology.

To address the issue of the intermittent noise in optical fringe pattern, an adaptive method of noise reduction is given based on empirical mode decomposition (EMD) and Hilbert Huang transform (HHT), and then the wrapped phase is obtained by performing the Hilbert transform on the refined pattern. Firstly, the signal of the fringe pattern is decomposed into several intrinsic mode functions (IMFs). With the instantaneous frequencies and marginal spectra of each IMF obtained by HHT, the criterion of identifying the noise IMF is determined. Then, it is judged whether a mode-mixing problem, which is the frequent problem in traditional EMD, appears in each noise IMF. If the problem appears, the "noise," which is designed according to the signal adaptively, is added to the original signal, and then the obtained new signal is decomposed again. The process will be repeated until there is no mode mixing in the noise IMF. Finally, the wrapped phase is obtained by performing a Hilbert transform on the refined pattern with noise and background components removed. The proposed method can solve the mode-mixing problem effectively. It can reduce most of the noise and maintain a large amount of detailed phase information simultaneously. Simulation and compared experiments show the efficiency, robustness, and accuracy of the proposed method.

This paper reports our investigations on the design of globally or quasi-globally optimal structures for three-component and four-component mechanically compensated zoom lenses. This is accomplished by implementation of a global optimization technique based on evolutionary programming. The technique searches optimal structures in the configuration space formed by the specific design variables: powers of individual components and the intercomponent separations. Any requirements for system length and Petzval curvature of the zoom lens can be incorporated in the search for optimal solutions. Illustrative numerical results of our investigations on four regular types of zoom systems, as classified by Tanaka, are presented.

We propose a wide field-of-view optical receiver design based on a fisheye lens and an off-axis catadioptric structure for free-space optical communications. The design utilizes a novel fisheye lens group to compress a wide field angle into a narrow field angle and produce the appropriately collimated light that can effectively be coupled into the following aperture of a catadioptric telescope. An off-axis catadioptric telescope with aspheric surface mirrors is designed to compress the incident beam spot size, compensate for the high order optical aberrations and eliminate light loss due to an obstruction. The parallel exit rays are reflected on a double-level tracking mechanism by feeding the position signal from a quadrant detector to correct the pointing error and optimize the coupling efficiency into an optical fiber. The final wide field-of-view optical receiver design is presented along with the evaluation of optical performance results and tracking characteristics. The proposed optical receiver not only can provide a 60-deg wide field-of-view to expand the tracking range, but also mitigates optical aberrations to improve the tracking accuracy for free space optical communication systems in a turbulent atmosphere.

We present the design and implementation of an 8-view three-dimensional (3-D) video player system based on a multi-core processor environment, which operates faster than existing video player systems. We propose a structure for obtaining near-optimum speed by parallelizing the component modules to process large volumes of 8-view image data at a high speed. In order to exploit task parallelism in the video player, we have designed a multiple-video decoder, a view synthesizer that creates the 3-D image from the multi-view image data, and a 3-D renderer for an 8-view display in a pipeline structure. For load balancing and exploiting data parallelism in the modules, the decoder is divided into units of viewpoint, and the view synthesizer is geometrically divided based on the synthesized images. As a result of this experiment, 8-view images are correctly synthesized, and the sense of three dimensions can be observed when watching the images on the 8-view auto-stereoscopic display. The proposed structure could be used to process large volumes of multi-view image data at high speeds by utilizing the maximum capacity of the multi-core processors.

In the past five years, significant progress has been accomplished in the reduction of infrared detector pitch and detector size. Recently, longwave infrared (LWIR) detectors in limited quantities have been fabricated with a detector pitch of 5 μm. Detectors with 12-μm pitch are now becoming standard in both midwave infrared (MWIR) and LWIR sensors. Persistent surveillance systems are pursuing 10-μm detector pitch in large format arrays. The fundamental question that most system designers and detector developers desire an answer to is: "How small can you produce an infrared detector and still provide value in performance?" If a system is mostly diffraction-limited, then developing a smaller detector is of limited benefit. If a detector is so small that it does not collect enough photons to produce a good image, then a smaller detector is not much benefit. Resolution and signal-to-noise are the primary characteristics of an imaging system that contribute to targeting, pilotage, search, and other human warfighting task performance. We investigate the task of target discrimination range performance as a function of detector size/pitch. Results for LWIR and MWIR detectors are provided and depend on a large number of assumptions that are reasonable.

We proposed and demonstrated a digital method of dispersion compensation suitable for spectral-domain optical coherence tomography. The wavelength coordinate of the coherence spectrum was calibrated digitally using a two-order polynomial. A software-based scheme was introduced to determine the polynomial coefficients of the polynomial fitting spectrum wavelength. Therefore, the spectrum deformation introduced by dispersion can be compensated effectively. This method was experimentally validated by in vivo imaging an early-stage chick embryonic heart.

Gaze tracking determines what a user is looking at; the key challenge is to obtain well-focused eye images. This is not easy because the human eye is very small, whereas the required resolution of the image should be large enough for accurate detection of the pupil center. In addition, capturing a user's eye image by a remote gaze tracking system within a large working volume at a long Z distance requires a panning/tilting mechanism with a zoom lens, which makes it more difficult to acquire focused eye images. To solve this problem, a new auto-focusing method for remote gaze tracking is proposed. The proposed approach is novel in the following four ways: First, it is the first research on an auto-focusing method for a remote gaze tracking system. Second by using user-dependent calibration at initial stage, the weakness of the previous methods that use facial width in captured image to estimate Z distance between a user and camera, wherein each person has the individual variation of facial width, is solved. Third, the parameters of the modeled formula for estimating the Z distance are adaptively updated using the least squares regression method. Therefore, the focus becomes more accurate over time. Fourth, the relationship between the parameters and the face width is fitted locally according to the Z distance instead of by global fitting, which can enhance the accuracy of Z distance estimation. The results of an experiment with 10,000 images of 10 persons showed that the mean absolute error between the ground-truth Z distance measured by a Polhemus Patriot device and that estimated by the proposed method was 4.84 cm. A total of 95.61% of the images obtained by the proposed method were focused and could be used for gaze detection.

Moving imagery from a static scene was recorded with an uncooled thermal imager at nine different angular velocities ranging from 0 (static) to 1 pixel/frame (3.75 deg/s) using a tilted rotating mirror. The scene contained a thermal acuity test chart with triangular test patterns based on the triangle orientation discrimination (TOD) test method. The imagery was processed with different types of image enhancement: dynamic super-resolution (DSR), local adaptive contrast enhancement (LACE), and combinations. DSR shows a significant performance improvement at low velocities, a moderate improvement at medium velocities where smear becomes apparent, and no benefit at high speed. Performance with LACE is close to optimized gain and level setting by hand. Static performance and dynamic performance at 0.57 pixel/frame containing significant smear were compared with earlier published identification performance data for two-hand held systems collected under a variety of signal processing conditions. It shows that the ratio M₇₅ between the 75% correct threshold size for the two-hand held objects and the TOD triangle is preserved under all conditions measured. Thus, TA range prediction based on the TOD is robust against a complex combination of conditions, including motion, smear, and the types of image enhancement applied.

We present a detailed design study for a novel solid-state focal plane array of silicon avalanche photodiodes (APDs) using an advanced silicon-on-sapphire substrate incorporating an antireflective bilayer consisting of crystalline aluminum nitride (AlN) and amorphous, non-stoichiometric, silicon rich, silicon nitride (a-SiNX<1.33) between the silicon and sapphire. The substrate supports electrical and optical integration of a nearly 100% quantum efficiency, silicon APD capable of operating with wide dynamic range in dual linear or Geiger-mode, with a gallium nitride (GaN) laser diode in each pixel. The APD device and epitaxially grown GaN laser are fabricated within a crystallographically etched silicon mesa. The high resolution 27 μm emitter-detector pixel design enables single photon sensitive, solid-state focal plane arrays (FPAs), with passive and active imaging capability in a single FPA. The square 27 μm emitter-detector pixel achieves SNR>10 in active detection mode for Lambert surfaces at 20,000 m.

The anterior refracting surface of the eye when wearing a contact lens is the thin fluid layer that forms on the surface of the contact lens. Under normal conditions, this fluid layer is less than 10 μm thick. The fluid layer thickness and topography change over time and are affected by the material properties of the contact lens and may affect vision quality and comfort. An in vitro method of characterizing dynamic fluid layers applied to contact lenses mounted on mechanical substrates has been developed by use of a phase-shifting Twyman-Green interferometer. This interferometer continuously measures light reflected from the surface of the fluid layer, allowing precision analysis of the dynamic fluid layer. Movies showing this fluid layer behavior can be generated. Quantitative analysis beyond typical contact angle or visual inspection methods is provided. Different fluid and contact lens material combinations have been evaluated, and variations in fluid layer properties have been observed. This paper discusses the interferometer design and analysis methods used. Example measurement results of different contact lens are presented.

An active stereo method for three-dimensional shape measurement is proposed. The proposed method uses epipolar constraint and binary coding structured light to perform dense and accurate stereo matching. The correspondence in horizontal directions is determined by epipolar constraint, and the binary code determines the correspondence in vertical directions. A high redundancy skeleton coding method is proposed to improve the decoding accuracy significantly. And the matching algorithm is achieved sub-pixel accuracy. The point cloud is calculated by triangulation. Spatial re-sampling based on the Delaunay triangulation and inverse distance weighting interpolation is implemented to get a uniform data density for a comfortable visualization. Compared with phase-shift methods, the proposed one is more robust. It preforms reliably even in noisy conditions. The experiment results are presented to demonstrate the effectiveness of the proposed method. The resolution is analyzed and verified by experiment. It achieves 1/1200 by two 2-megapixel cameras and can improve by increasing the image resolution. The robustness is also verified. The experiment demonstrated that our method has great immunity of three main type of noise in the phase-shift method.

For the past two decades, the need for three-dimensional (3-D) scanning of industrial objects has increased significantly and many experimental techniques and commercial solutions have been proposed. However, difficulties remain for the acquisition of optically non-cooperative surfaces, such as transparent or specular surfaces. To address highly reflective metallic surfaces, we propose the extension of a technique that was originally dedicated to glass objects. In contrast to conventional active triangulation techniques that measure the reflection of visible radiation, we measure the thermal emission of a surface, which is locally heated by a laser source. Considering the thermophysical properties of metals, we present a simulation model of heat exchanges that are induced by the process, helping to demonstrate its feasibility on specular metallic surfaces and predicting the settings of the system. With our experimental device, we have validated the theoretical modeling and computed some 3-D point clouds from specular surfaces of various geometries. Furthermore, a comparison of our results with those of a conventional system on specular and diffuse parts will highlight that the accuracy of the measurement no longer depends on the roughness of the surface.

We propose a novel framework to simultaneously and accurately measure the three-dimensional (3-D) shape and 3-D motion of a dynamic deformable surface from a calibrated stereo image sequence. The framework mainly aims at the problems of error accumulation and local illumination change. It performs the measurement with a random gray triangle pattern marked on the object surface via the following steps: first, the triangles in all images are detected using a method we proposed; second, the matching triangles between the first, left, and right frame in the stereo image sequence are located by the proposed local triangle descriptor and an extension of the epipolar constraint to triangles; third, the spatiotemporal triangle correspondences in the subsequent frames are obtained by triangle tracking, and the tracking errors are detected and recovered by the local 3-D topology. The performance is evaluated in challenging simulated experiments, and the effectiveness is demonstrated by real surfaces. The experimental results show that the proposed framework is effective and robust to cope with error accumulation and the influence of local illumination change.

Due to the lateral alignment incapability of planar subaperture stitching algorithms, subaperture testing (SAT) is still challenging especially for quasi-planar free-form wavefronts featured with vertical fluctuation of small amplitude and high frequency. To avoid the lateral misalignment-induced error, we propose a stitching algorithm with quasi-planar free-form surface registration. The subapertures are considered as three-dimensional point sets acquired from a free-form surface instead of the error surface superposed on a plane. Then all subapertures are stitched together by minimizing the deviations among overlaps with regard to the free-form surface. Finally cross-test simulations and experiments are presented to show the effect of error reductions in SAT of large continuous phase plate wavefronts, verified by the full-aperture testing with a large-aperture interferometer.

Our work aims to identify nano-scale metal films with enhanced absorption in the terahertz (THz) spectral range (1 to 10 THz) that can be incorporated in thermal imagers that operate in this spectral band. Absorption measurements of chromium and nickel films with different thicknesses (2.5 to 50 nm) revealed that absorption as high as 47% can be achieved by controlling the thickness of the film. The measured absorption agrees well with the predicted maximum absorption of 50% using thin metal films. The results indicate that nanometer scale metal films can provide high THz absorption for applications in thermal sensing.

We propose a new design for slow-light photonic crystal W1 waveguide, which uses a combination of circular and elliptical air holes arranged in a hexagonal lattice with background material of refractive index n = 2.84. Large value of normalized delay bandwidth product (NDBP = 0.3708) is obtained. We have also analyzed dispersion property for the structure and achieved nearly "zero-dispersion" for a very large bandwidth. Our proposed photonic crystal waveguide has slow light applications such as reduction in length and power consumption of all-optical and electro-optic switches at optical frequency.

We present the results of the radiometric characterization of an "M" structure long wavelength infrared Type-II strained layer superlattice (SLS) infrared focal plane array (IRFPA) developed by Northwestern University (NWU). The performance of the M-structure SLS IRFPA was radiometrically characterized as a function of photon irradiance, integration time, operating temperature, and detector bias. Its performance is described using standard figures of merit: responsivity, noise, and noise equivalent irradiance. Assuming background limited performance operation at higher irradiances, the detector quantum efficiency for the SLS detector array is approximately 57%. The detector dark density at 80 K is 142  μA/cm², which represents a factor of seven reduction from previously measured devices.

^{Using by different output transmittances of 2%, 5%, and 10%, we have investigated the continuously tunable laser performance of c-cut Tm:YAP crystal. The 5-mm long c-cut crystal with 4 at.% thulium ion was used. Without a tuning element, the slope efficiency respect to the absorbed pump power reached 44.1% with transmittance of 5%, corresponding to the conversion efficiency of 35.3%. The laser operated at TEM00 mode with a beam quality factor of M2 _{~ 1.3, which was demonstrated by a 90/10 knife-edge method. A 3-mm thick birefringent plate was used as a tuning element. At transmittance of 5%, the widest tunable range of 159 nm extended from 1899 to 2058 nm. For transmittances of 2% and 10%, the tunable ranges of 150 and 68 nm were achieved, respectively.}}

An efficient and compact all-solid-state continuous wave 67-nm red laser is generated by intracavity frequency doubling of a diode pumped Nd∶YVO₄ laser at 1342 nm while suppressing the higher gain transition near 1064 nm. With the incident pump power of 40 W and a frequency doubling crystal lithium triborate, as high as 10.5-W output power at 671 nm is achieved. The optical-to-optical conversion efficiency is 26.3% and the output power stability during 8 h of operation is better than 2.3%. To the best of our knowledge, this is the highest conversion efficiency of watt-level laser at 671 nm generated by intracavity frequency doubling of a diode pumped Nd∶YVO₄ laser at 1342 nm.

Ocular interferometry has potential value in a variety of ocular measurement applications, including measuring ocular thicknesses, topography of ocular surfaces or the wavefront of the eye. Of particular interest is using interferometry for characterizing corneal shape and irregular corneal features, making this technology attractive due to its inherent accuracy and spatial resolution. A particular challenge of designing an ocular interferometer is determining safe laser exposure levels to the eye, including both the retina and anterior segment. Described here are the laser exposure standards relevant in the interferometer design and the corresponding calculations and results. The results of this work can be used to aid in the design of similar laser-based systems for ocular evaluation.

We have experimentally observed bright-dark soliton pairs in an erbium-doped fiber ring laser for the first time. This approach is different from the vector dark domain wall solitons which separate the two orthogonal linear polarization eigenstates of the laser emission. In our laser, the bright-dark soliton pairs can co-exist in any one polarization state. Numerical simulations based on the coupled complex Ginzburg-Landau equations have confirmed the experimental results.

Both methods to control the gain in the modulation chain of interferometric fiber optic gyroscope (IFOG) are analyzed: One is based on the square wave biasing modulation, and the other is based on the four-state wave biasing modulation. The analysis results indicate that the method based on square wave is less efficient at low angular rate because of long reset time, and the method based on four-state wave may give the wrong or reverse gain error at high angular rate because of frequent resets. To eliminate the limitation of the existing methods, a novel demodulation method of the gain in the modulation chain based on periodical biasing modulation is proposed. This method is independent of the 2Π phase ramp resets and the input angular rate. Experimental results indicate that the method effectively improves the scale factor stability and linearity of closed-loop IFOG.

The spectrum shift of erbium-doped magneto-optic fiber Bragg grating (Er-MFBG) induced by external magnetic fields is, for the first time, directly measured by the method of the "direct edge detection," and then the effective Verdet constant of −12.42  rad/(T·m) is determined. The theoretical results are in agreement with the experimental data. Our analysis shows the transfer characteristics of the spectrum shift to the transmission power are dependent on the state of polarization and wavelength position of probe light for a given Er-MFBG.

A novel method using half-symbol delay tap sampling technique for monitoring timing misalignment between data modulator and pulse carver in 33% duty-cycle return-to-zero on-off keying (RZ-OOK), 50% duty-cycle RZ-OOK, and carrier-suppressed RZ-OOK optical transmitters is proposed and experimentally demonstrated. The presented scheme is able to not only identify three RZ-OOK signals but also determine both the timing misalignment magnitude and direction. The effectiveness of the proposed scheme is validated by simulation and experiment in 10-Gbps optical systems, and its robustness against imperfections of the transmitter is also analyzed.

Different launching methods over multimode fiber (MMF) are reviewed and compared under various aspects such as coupling coefficient, mode power distribution, and bit error rate performance. Among these, center launch and ring launch are elaborated and chosen as the inputs of multiple-input multiple-output (MIMO) scheme for center launch exciting limited lower-order modes while ring launch exciting limited higher ones. Furthermore, we discuss the theoretical background and give a new wide-band MMF MIMO mathematical model. This paper also proposes a novel MMF MIMO system combining the dual restricted launches together with multi-segments receiving. The simulated results indicate that an aggregate data rate of 20 Gb/s over 800-m graded index-multimode fiber can be achieved by using this newly established MIMO scheme.

A function is constructed to approximate the fundamental mode field precisely in photonic crystal fibers (PCFs) using least square error criteria. Through the unconstrained nonlinear programming method, the optimum parameters of the constructed function are derived, and the optimum constructed function is found. For photonic crystal fibers, using such an optimum constructed function, small errors are brought out when approximating their fundamental mode fields regardless of d/Λ values. Furthermore, the constructed function is not only suitable for index-guiding PCFs, but also for bandgap PCFs with hollow core to some extent. Based on this constructed function, an analytic expression for the far field of the approximated fundamental mode field is deduced. Numerical results demonstrate that the analytic expression brings out small errors compared with the actual far field.

Within the scalar framework, a simple and complete formulation for the normalized propagation constants of the infinite cladding region of a photonic crystal fiber (PCF) with triangular lattice of air-holes is presented, which is dependent only on the ratio of air-hole diameters and their separation. The accuracy of the proposed formulation is depicted by comparing our results with those obtained by Russell. Then the refractive indices of the fundamental space-filling mode (nFSM) in the cladding region of the PCF from Russell's equation and the proposed relations are evaluated and the two indices are observed to match quite excellently for different values of relative air-hole size and wavelength. An equivalence between the two approaches of Russell and Saitoh is also sought. Finally, in order to check the validity of the formulation in problems of practical interest, the proposed relations are applied to evaluate the total chromatic dispersion in a PCF, treating it as a conventional step index fiber having its core and cladding indices as those of silica and nFSM, respectively. On comparison with the available results of Saitoh, the results match nicely.

We report the formulation of the adaptive variable coefficient predictor-corrector Adams-Bashforth scheme for modeling the population dynamics in erbium-doped fiber amplifiers and lasers based on highly doped fibers. A modified form of the scheme derived using a Lagrange polynomial is shown to result in 75% reduction of step-size as compared to a conventional adaptive Euler method. Our analysis shows that the second-order predictor and third-order corrector is most suitable for accurate modeling of the above problem. The model has been validated by re-generating the absorption and emission spectrum for doped fibers found in the literature. This modeling approach has been carried further to simulate a filterless fiber laser cavity, in which several gain and saturation dynamics are encountered. Spectral power evolution in the fiber is simulated by using the above method, and the steady-state lasing wavelength is evaluated as a function of cavity attenuation. The experimental results are found to match very well with the simulation.

We describe an analog microwave photonic link system, which is used to transmit in a multiplexed way a TV signal over 30 km of standard optical fiber. The experimental setup is composed mainly by two distributed feedback (DFB) laser diodes emitting at 1500 nm. When these DFB lasers are operated in the low laser threshold current region, relaxation oscillation frequencies are obtained. Relaxation oscillations in the laser intensity can be seen as sidebands on both sides of the main laser line. The optical emissions generated in each laser are combined and amplified by using an erbium-doped fiber amplifier. Next, the amplified optical signal is detected by a fast photo-detector using direct detection method, and as result of this photo-detection, microwave signals are generated. Since microwave signals obtained by using this technique are tuned continuously; we can use them as electrical carriers to transmit simultaneously a TV signal at 4 and 5 GHz and over 30 km of standard optical fiber by using a Mach-Zehnder modulator. At the end of the optical link the modulated light is photo-detected in order to recover efficiently and successfully the analog TV signal.

We proposed newly two-dimensional (2-D) spectral amplitude coding optical code division multiple access (OCDMA) scheme using modified double weight (MDW) code capable of suppressing phase-induced intensity noise (PIIN). The architecture of the spectral/spatial MDW OCDMA system with the property of multi-access interference cancellation is presented. The proposed code exhibits good cross-correlation property. At the optimized data transmission rate of 0.745 Gbps, 2-D MDW, M = 63, N = 3, reaches maximum cardinality of 200% increases compared to 2-D perfect difference code, M = 57, N = 3. The performance is severely deteriorated if the data rate further increases above 0.745 Gbps. The proposed code meets the optical transmission requirements at 10−9 bit error rate error floor, with lowest effective transmitted power (Psr), −17.5  dBm, in comparison to the others through minimizing interference noise that result in PIIN suppression. The proposed system reaches optimum requirements performance in terms of cardinality, data transmission rate, and low effective transmitted power.

Pulse response of the underwater wireless optical channel is significant for the analysis of channel capacity and error probability. Traditional vector radiative transfer theory (VRT) is not able to deal with the effect of receiving aperture. On the other hand, general water tank experiments cannot acquire an accurate pulse response due to the limited time resolution of the photo-electronic detector. We present a Monte Carlo simulation model to extract the time-domain pulse response undersea. In comparison with the VRT model, a more accurate pulse response for practical ocean communications could be achieved through statistical analysis of the received photons. The proposed model is more reasonable for the study of the underwater optical channel.

The Brillouin backscattered signal of LIDAR can be used in remote sensing of ocean parameters such as temperature. Current methods for measuring ocean temperature are based on the monotropic function between Brillouin shift and ocean temperature, while the effect of the ocean salinity, which influences the measurement of temperature, is neglected. However, the variations in salinity will also lead to nonignorable change of the temperature. Neglecting it will result in an inaccurate measurement of temperature. We first propose a new model that takes both Brillouin shift and linewidth as independent variables, and then establish the multi-valued equations of these variables and ocean parameters. With a data fitting procedure the ocean temperature and salinity can be measured simultaneously. The accuracy of this model and the uncertainty of the measurement are analyzed. Theoretical and experimental analysis showed that the ocean temperature and salinity can be simultaneously obtained by measured Brillouin frequency shift and linewidth.

In the process of road extraction, the road region often mixes with some redundancies caused by the phenomenon of "different objects with the same spectrum," which exists widely in remote sensing images. To eliminate these redundancies and preserve neat and accurate road regions, a method based on skeleton analysis is proposed. At first, the shortest path of a specified road segment is constructed with mixed region skeletons. The road width at the skeleton point is then selected as the smoothing scale on this point, on which basis an accumulative and bidirectional smoothing is taken. With the smoothed path and its average width, a buffer algorithm reconstructs the road region. The results show that redundancies of the road can be eliminated correctly, and accurate road center lines and neat road regions can be obtained.

Over the past four decades, the satellite imaging sensors have acquired huge quantities of Earth- observation data. Content-based image retrieval allows for fast and effective queries of remote sensing images. Here, we take the following two issues into consideration. Firstly, different features and their combination should be chosen for different land covers. Secondly, for the block dividing strategy and the complexities of the remote sensing images, it can not effectively retrieve some small target areas scattered in multiple nontarget blocks. Aiming at the above two issues, a new region-based retrieval method with adaptive image segmentation is proposed. In order to improve the accuracy of remote sensing image segmentation, feature selection and weighing is performed by two-stage clustering, and image segmentation is accomplished based on the chosen features and mean shift procedure. Meanwhile, for the homogeneous characteristics of remote sensing land covers, a new regional representation and matching scheme are adopted to perform image retrieval. Experimental results on retrieving various land covers show that the method can avoid the impact of traditional blocking strategies, and can achieve an average percentage of 19% higher precision with the same level of recall rate, than the relevance feedback method for small target areas.

A new spatiotemporal target detection method that utilizes the recursive temporal profile (RTP) and the spatiotemporal gradient pattern (STGP) is proposed for infrared (IR) image sequence. In the IR search and tracking system, long-distance aerial targets compared with short-distance aerial targets appear to be composed of several pixels with no special shapes and their movements are slow. Considering the characteristics of aerial targets, an algorithm based on the STGP and fuzzy-set theory is proposed to detect long-distance aerial targets while the recursive temporal profile algorithm based on the temporal profile and mean estimation is proposed to detect short-distance aerial targets. In addition, the RTP and the STGP are combined to detect the aerial targets that exist at diverse distances in the IR image sequence. The performance of the proposed method is examined by using the receiver operating characteristic curve. The experiment results show that the proposed method performs better than the existing methods in terms of target detection and clutter removal.

In recent years image-processing has become a central part of optical inspection and measurement systems. Typically, after measuring the given specimen by utilizing a suitable sensor, image-processing algorithms are used to detect dedicated features such as surface defects. These algorithms are usually designed, optimized, and tested by an image-processing expert according to the task specifications. A methodology (based on genetic programming) is presented to automatically generate, optimize, and test such algorithms without the necessity of an image-processing expert. We also present several examples of inspection tasks to support the concept. For efficiency, an automated multi-scale multi-sensor inspection strategy is employed.

A widely used contrast enhancement method, the histogram equalization (HE) often produces images with unnatural appearances and visually disturbing artifacts because the HE compels the enhanced image to follow the uniform distribution. An adaptive histogram equalization using logarithmic mapping is presented, with a proposed algorithm based on a bin underflow and overflow method that achieves contrast enhancement by putting constraints on each histogram component differently. To incorporate characteristics of the human visual system, the logarithmic mapping function is used as constraint function, while the rate of contrast enhancement is controlled by determining the control parameters with the characteristics of the original image. The experimental results show that the proposed algorithm not only keeps the original histogram shape features, but also enhances the contrast effectively. Due to its simplicity, the proposed algorithm can be applied by simple hardware and processed in a real-time system.

Background clutter can obscure or mimic the desired target and confuse the operator. Thus, the similarity between the background and the target is a typical feature of the background clutter. A clutter metric based on human contrast sensitivity function is proposed. It measures the similarity between the background and the target in the frequency domain, after the differences that cannot be seen by the visual system have been "thrown away" and the visible differences have been weighted according to the sensitivity of the visual system. The correlation between the experimental probability of detection and that predicted by the clutter metric are presented. Experiment results show that the contrast-sensitivity-function-based clutter metric can perform other clutter metrics in open literature in quantifying background clutter.

A direct method of motion estimation and structure reconstruction for various motion forms has been proposed based on optical flow. First, a motion estimation energy function is established by redesigning the data term and the smoothing term under the assumption of three-dimensional motion constancy. Next, the Euler-Lagrange iterative formula for motion estimation is obtained with the variational method. Finally, the relative depth and a dense structure are recovered from the estimated motion velocities. Experimental results show that the proposed method is more precise and robust for estimating and reconstructing various motion forms.

The shearlet representation forms a tight frame which decomposes a function into scales and directions, and is optimally sparse in representing images with edges. An image fusion method is proposed based on the shearlet transform. Firstly, transform the image A and image B by the shearlets. Secondly, a pulse couple neural network (PCNN) is used for the frequency subbands, which uses the number of output pulses from the PCNN's neurons to select fusion coefficients. Finally, an inverse shearlet transform is applied on the new fused coefficients to reconstruct the fused image. Some experiments are performed in images such as multi-focus images, multi-sensor images, medical images and multispectral images comparing the proposed algorithm with the wavelet, contourlet and nonsubsampled contourlet method based on the PCNN. The experimental results show that the proposed algorithm can not only extract more important visual information from source images, but also effectively avoid the introduction of artificial information. It significantly outperforms the traditional multiscale transform image fusion methods in terms of both visual quality and objective evaluation criteria such as MI and Q^AB/F.

We present a multi-stage classification approach to detect targets in widely varying thermal imagery. A multi-level spatial-temporal median filter is utilized to extract the background frame, with which the background clutters are suppressed by using the principal component analysis technique. A spatially related fuzzy adaptive resonance theory (ART) neural network is then applied to identify the local regions-of-interest. Within each region, another fuzzy ART neural network is utilized to detect the targets. Experimental results demonstrate that the proposed approach is capable of detecting infrared moving targets effectively for F1 measurement up to 96.3%.

In the denoising literature, research based on the nonlocal means (NLM) filter has been done and there have been many variations and improvements regarding weight function and parameter optimization. Here, a NLM filter with patch-based difference (PBD) refinement is presented. PBD refinement, which is the weighted average of the PBD values, is performed with respect to the difference images of all the locations in a refinement kernel. With refined and denoised PBD values, pattern adaptive smoothing threshold and noise suppressed NLM filter weights are calculated. Owing to the refinement of the PBD values, the patterns are divided into flat regions and texture regions by comparing the sorted values in the PBD domain to the threshold value including the noise standard deviation. Then, two different smoothing thresholds are utilized for each region denoising, respectively, and the NLM filter is applied finally. Experimental results of the proposed scheme are shown in comparison with several state-of-the-arts NLM based denoising methods.

Image deconvolution is an ill-posed, low-level vision task, restoring a clear image from the blurred and noisy observation. From the perspective of statistics, previous work on image deconvolution has been formulated as a maximum a posteriori or a general Bayesian inference problem, with Gaussian or heavy-tailed non-Gaussian prior image models (e.g., a student's t distribution). We propose a Parseval frame-based nonconvex image deconvolution strategy via penalizing the l₀-norm of the coefficients of multiple different Parseval frames. With these frames, flexible filtering operators are provided to adaptively capture the point singularities, the curvilinear edges and the oscillating textures in natural images. The proposed optimization problem is implemented by borrowing the idea of recent penalty decomposition method, resulting in a simple and efficient iteration algorithm. Experimental results show that the proposed deconvolution scheme is highly competitive among state-of-the-art methods, in both the improvement of signal-to-noise ratio and visual perception.

We propose an efficient texture-preserving image deconvolution algorithm. This algorithm restores a blurred image by incorporating a wave atom-based Wiener shrinkage filter with a spatial-based joint non-local means filter. Wave atom is a new transform which is half multi-scale and half multi-directional. This transform offers a better representation of images containing oscillatory patterns and textures than other known transforms. Our method first restores the image in the frequency domain to obtain a noisy result with minimal loss of image components, followed by a Wiener shrinkage filter in the wave atom domain to attenuate the leaked colored noise. Although the wave atom-based method is efficient in texture-preserving image denoising, it is prone to producing edge ringing which relates to the structure of the underlying wave atom. In order to reduce the ringing, we developed an efficient joint non-local means filter by using the wave atom deconvolution result. This filter could suppress the leaked colored noise while preserving image details. We compare our deconvolution algorithm with many competitive deconvolution techniques in terms of ISNR and visual quality.

We propose an adaptive search range adjustment algorithm that is particularly suitable for low-bit-depth motion estimation approaches. Typical low-bit-depth motion estimation approaches, such as one-bit transform (1BT), two-bit transform (2BT), and truncated gray-coded bit-plane matching (TGCBM), perform a full search with low-bit expression. We propose combining a search-range adjustment, which can be predicted by using motion vector information of the reference frame and the existing bit-wise matching methods, such as 1BT, 2BT, and TGCBM. Combining this proposed algorithm and low-bit expression enhances both motion estimation accuracy and time consumption. Experimental results show that low-bit-depth motion estimation approaches using this proposed algorithm have an outstanding performance compared with those without the proposed algorithm both in motion estimation accuracy and time consumption.

We propose a discrete cosine transform (DCT) analysis-based adaptive deblocking algorithm to reduce the block discontinuities. First we analyze the properties of the one-dimensional DCT coefficients. Based on this analysis, we utilize two adjacent vectors to classify the vector-containing block boundary into three models. For each model, we apply different filters according to the local properties. Comprehensive experiments indicate that the proposed method outperforms a large number of deblocking methods in the literature in terms of the evaluation of peak signal-to-noise ratio, perceptual quality, and computational complexity.

We present a novel scheme of feature extraction, namely kernel Laplacian maximum margin criterion, for face recognition. The proposed method seeks to maximize the difference, rather than the ratio, of the determinant between the between-class Laplacian scatter matrix and within-class Laplacian scatter matrix in the implicit feature space via kernel trick. The proposed method not only can produce nonlinear discriminant features, but also does not need to calculate the inverse within-class Laplacian scatter matrix. Experimental results on ORL, FERET, and AR databases validate the effectiveness of the proposed method.

Generally, the designs of digital image processing algorithms and image gathering devices remain separate. Consequently, the performance of digital image processing algorithms is evaluated without taking into account the influences by the image gathering process. However, experiments show that the image gathering process has a profound impact on the performance of digital image processing and the quality of the resulting images. Huck et al. proposed one definitive theoretic analysis of visual communication channels, where the different parts, such as image gathering, processing, and display, are assessed in an integrated manner using Shannon's information theory. We perform an end-to-end information theory based system analysis to assess linear shift-invariant edge-detection algorithms. We evaluate the performance of the different algorithms as a function of the characteristics of the scene and the parameters, such as sampling, additive noise etc., that define the image gathering system. The edge-detection algorithm is regarded as having high performance only if the information rate from the scene to the edge image approaches its maximum possible. This goal can be achieved only by jointly optimizing all processes. Our information-theoretic assessment provides a new tool that allows us to compare different linear shift-invariant edge detectors in a common environment.

We propose a novel content-aware three dimensional (3-D) image (two dimensional (2-D)-plus-depth) retargeting method using a 3-D saliency-based energy function that effectively describes perceptual importance of objects in 3-D space. The 2-D and depth images are retargeted together by carving out collinear seam paths corresponding to the one having the least 3-D saliency energy. However, resizing individual objects in different ratios without depth modification can cause surface shape distortion of the 3-D objects. To minimize such distortion, depth values for the objects are adaptively remapped examining depth histogram change. Experimental results indicate that the proposed method can preserve structures of important objects in 3-D space much more effectively than conventional methods.

Here, we present a novel object of interest (OOI) extraction framework designed for low-frame-rate (LFR) image sequences, typically from mobile mapping systems (MMS). The proposed method integrates tracking and segmentation in a unified framework. We propose a novel object-shaped kernel-based scale-invariant mean shift algorithm to track the OOI through the LFR sequences and keep the temporal consistency. Then the well-known GrabCut approach for static image segmentation is generalized to the LFR sequences. We analyze the imaging geometry of the OOI in LFR sequences collected by the MMS and design a Kalman filter module to assist the proposed tracker. Extensive experimental results on real LFR sequences collected by VISAT™ MMS demonstrate that the proposed approach is robust to the challenges such as low frame rate, fast scaling, and large inter-frame displacement of the OOI.

We show an original method for automatic hand gesture recognition that makes use of fuzzified latent-dynamic conditional random fields (LDCRF). In this method, fuzzy linguistic variables are used to model the features of hand gestures and then to modify the potential function in LDCRFs. By combining LDCRFs and fuzzy sets, these fuzzy-based LDCRFs (FLDCRF) have the advantages of LDCRFs in sequence labeling along with the advantage of retaining the imprecise character of gestures. The efficiency of the proposed method was tested with unsegmented gesture sequences in three different hand gesture data sets. The experimental results demonstrate that FLDCRFs compare favorably with support vector machines, hidden conditional random fields, and LDCRFs on hand gesture recognition tasks.

The authors propose a fragment-based variational filtering technique for human tracking. Based on human classifiers and histograms of oriented gradients descriptor, more informative local parts of the human body are selected in the reference model and updated during the tracking process. Hyper-parameters of the variational Bayesian filter are adaptively tuned in order to cope with variable scenes and occlusions. To speed up the initialization and reference updating, an efficient motion cue is fused with the human detection. Extensive experimental results on benchmark datasets show that the proposed tracker is effective and robust.

Scene text detection is an important step for the text-based information extraction system. This problem is challenging due to the variations of size, unknown colors, and background complexity. We present a novel algorithm to robustly detect text in scene images. To segment text candidate connected components (CC) from images, a text probability map consisting of the text position and scale information is estimated by a text region detector. To filter out the non-text CCs, a hierarchical model consisting of two classifiers in cascade is utilized. The first stage of the model estimates text probabilities with unary component features. The second stage classifier is trained with both probability features and similarity features. Since the proposed method is learning-based, there are very few manual parameters required. Experimental results on the public benchmark ICDAR dataset show that our algorithm outperforms other state-of-the-art methods.

Deinterlacing has been used to convert interlaced video signals into progressive video signals. Conventional deinterlacing methods with low levels of complexity can lead to deteriorating video quality, particularly in edge areas. Another problematic artifact is flickering, which occurs more frequently as the video size increases. For example, this flickering artifact is more frequently observed in high-definition television signals. In this paper, we propose a flickering artifact reduction algorithm for deinterlacing, which noticeably increases the overall visual quality.

In high efficiency video coding (HEVC) scheme, the split structure of the largest coding-unit (LCU) is highly variable and laborious due to its recursive quad-tree representation. Thus, the computational complexity of the HEVC encoder increases dramatically. A fast HEVC encoding method is proposed to predict the split structure of the current LCU by using the same structure of the co-located LCU in the reference or temporally-previous frame, in order to reduce the encoding computational complexity. Simulation results show that the proposed method can achieve a reduction in encoding time of 21.3% on average, with a negligible average PSNR loss and a negligible bit rate increase compared with the original HEVC encoding scheme.

We propose a quality assessment method from decoding parameters of compressed bitstreams by scalable video coding (SVC) as a hybrid/bitstream category. Conventional video quality assessment methods evaluate the video quality of degraded videos after full reconstruction. However, the proposed assessment method quantifies video quality of SVC not only with reconstructed videos for the base layer but also with decoding parameters for the enhancement layer. The proposed algorithm assesses the enhanced quality degree of the enhancement layers with statistics of various coding parameters for the enhancement layers with respect to the quality of the base layer. The accuracy of the proposed algorithm is 23% higher than those of conventional algorithms in terms of Pearson correlation. Furthermore, the proposed algorithm has significantly lower computational complexity than conventional methods.

Photonic bands in two types of two-dimensional metallic photonic crystals (2-D MPCs), which are composed of dielectric rods embedded into a metallic background (type I MPCs) and metallic rods in a dielectric background (type II MPCs), are investigated theoretically using a method based on the frequency-dependent plane-wave expansion method. We discuss the maximization of the normalized gap width as a function of the rod shapes and orientations. In addition, we study the effect of dielectric constants of the rods and the background on the width of the photonic band gap. Four different shapes of rods-square, circular, diamond, and rectangular-are considered. The numerical results show that the type I MPCs have a higher normalized gap width than the type II MPCs. We observe that the rotation of the noncircular rods in the type I MPCs leads to a slight variation, less than 10%, in the normalized values of the gap width in the two lattice structures. However, rotating the metallic square rods arranged in a square lattice results in doubling of the normalized gap width. The normalized gap width can be tailored by changing the dielectric constant of the rods (background) in type I (type II) MPCs.

A kind of angular-multiplexing optical image encryption scheme is proposed based on Fresnel-transform holography and random amplitude encoding. By introducing reference plane waves with different incident angles in the output plane, we accomplished multiple-image encryption. To enhance the feasibility of the system and decrease the coding complexity and precision requirement for random-phase mask, random-amplitude masks were positioned in the input plane and inserted into the reference arm, and some digital manipulations were applied in the encryption and decryption procedure. We analyzed the encryption and decryption quality of the proposed encryption method together with the influence of different random number generators. Numerical simulation proved the validity of the proposed scheme.

We describe quantum theory by using a complex valued random signal, which is (coherently) averaged over a time window, and a photon click is defined as the energy of this averaged signal surpassing a detector threshold. The random signal is modeled as white noise but grows over time s (proportional to √⁸). Eventually this random signal will lead to a detector "click" defined by a detector threshold condition, at which point the random signal is reset. Further we proceed by analysing correlations and finally by modeling the quantum state of an entangled pair by a complex valued correlation function.