Low-light remote sensing technology is crucial for surface observation during twilight and lunar phases; however, the acquired images often suffer from low contrast, low brightness, and low signal-to-noise ratios, which adversely affect observation quality. Traditional low-light image enhancement algorithms, such as Histogram Equalization, Gamma Correction, and Adaptive Histogram Equalization, can improve visual outcomes but also suffer from issues such as over-enhancement, loss of detail, noise amplification, and insufficient adaptability. To address these limitations, this paper proposes a low-light remote sensing image enhancement method based on Zero-Reference Deep Curve Estimation (Zero-DCE). This approach does not require paired samples and guides network learning through a non-reference loss function, making it particularly suitable for enhancing remote sensing images in low-light environments. Due to the lack of dedicated low-light remote sensing datasets, this study utilizes images from the UCMerced dataset to create simulated low-light remote sensing images for model fine-tuning. All color images are converted to grayscale to align with the characteristics of satellite-based low-light remote sensing images and to simplify the training process. Experimental results demonstrate that the proposed method significantly outperforms traditional techniques in terms of Structural Similarity Index (SSIM) and Peak Signal-to-Noise Ratio (PSNR), while also excelling in denoising and preserving texture authenticity. The optimized Zero-DCE++ not only maintains the original performance but also significantly reduces computational costs and enhances inference speed, which is of great importance for real-time low-light remote sensing image processing on satellite platforms.
It is difficult for traditional CMOS camera to obtain clear images under extremely low-light conditions for example the new moon or the quarter moon because the photons generated are so few that the signal-to-noise ratio (SNR) is much lower than what is necessary to resolve finer details. Being different from traditional CMOS camera, intensified CMOS, named as ICMOS camera can greatly amplify the very limited arriving photons through external photoelectric effect and thus the corresponding SNR could be improved a lot for low-light conditions. In previous studies, by fusing a series of low-light images having sub-pixel displacement between each other through classical iterative back projection (IBP) reconstruction algorithm, not only the resolution is enhanced but also the SNR increases as well. However why the SNR can be improved through super-resolution reconstruction is not theoretically answered yet. Therefore in this manuscript two contributions are made. In the first place, the characteristics of sub-pixel super-resolution low-light imaging are firstly further investigated. By introducing the concept of spectral SNR, the analytical expression of the SNR before and after super-resolution reconstruction is established, based on which it is concluded that the MTF boosting generated by super-resolution reconstruction is one important factor that can bring in the SNR increment besides inherent noise reducing characteristic of the super-resolution reconstruction algorithm itself. In the second place, by combing the IBP based super-resolution reconstruction algorithm, the FFT (Fast Fourier Transform) based single image amplification and image enhancement methods together, better reconstruction results could be obtained.
With the development of space satellite remote sensing technology, the demand of high-resolution imaging is increasing day by day. The aim of this paper is to explore a new kind of optical imaging, high-resolution rotating pupil optical imaging. By introducing rectangular rotating pupil and super-resolution reconstruction algorithm into the imaging system, this technology can significantly improve the resolution of the system, reduce aberrations and improve the image quality. Firstly, the theoretical basis of rotating pupil optical imaging is analyzed, including the effect of pupil rotation on the performance of the imaging system. The degradation images with different rotation angles are obtained, and the degradation mechanism and characteristics are analyzed. Then, a set of simulation model and method for image quality improvement of rotating pupil optical imaging system are designed and constructed. The final high-resolution image is obtained by the super-resolution reconstruction algorithm, and the theoretical analysis and performance index of this technology are verified and tested. Compared with traditional active super-resolution imaging system, rotating pupil optical imaging adopts passive imaging mode, which can significantly improve imaging resolution and reduce aberrations, especially in dynamic imaging and long-distance imaging. Finally, the future development trend of rotating pupil optical imaging is prospected, and the possible improvement direction and further research suggestions are put forward. This technology is expected to play an important role in the future field of space optical imaging, providing new solutions for high-resolution imaging.
A spherical coded imaging system combined with a controlled spherical aberration lens system and a digital sharpening filter can realize a fast and low-cost extended depth of field (EDoF) imaging system. At the same time, the wavefront coding technology is introduced, which can not only extend the depth of focus of the system, but also suppress the aberration including spherical aberration in the system design. However, for the wavefront coding system, due to the modulation of the incident light wave, the light distribution is more diffuse, so the blurred image generated by the wavefront coding system is a blurred image. It is necessary to decode and restore the intermediate blurred image to obtain a clear target image. In view of the lack of convergence and reliability of IBD algorithm, the Richardson-Lucy(RL) algorithm is introduced into RL-IBD algorithm, which can effectively reduce the sensitivity of the algorithm to noise. On the basis of vector extrapolation and exponential correction, this paper proposes improvements to the RL-IBD algorithm, which enhances the stability of the algorithm, and improves the convergence speed, noise suppression ability and adaptability of the algorithm.
In this paper, a whole general design and optimization process is detailedly demonstrated by taking the design and optimization of a 55mm diameter variable curvature mirror(VCM) with a cycloid-like thickness distribution as example. The finite-element analysis to the VCM under each change of main structure parameter is done and analyzed to choose the proper parameter value of each structure to obtain the optimum surface figure accuracy. Finally, the designed VCM can achieve 0.386mm central deflection and RMS 82.84nm within the effective aperture 28.4mm.
The camera is an important part of the optical telescope observing system, and the performance of the camera is an important factor affecting the quality and efficiency of astronomical observations. EMCCD can achieve lower noise and higher detection sensitivity by charge multiplication techniques, and can be used to realize direct observations of very faint and weak targets, and relative to the traditional CCD/CMOS detectors, the noise level can be reduced by an order of magnitude to reach the Sub-electron level. However, facing the need for calibration of ultra-low noise at the sub-electron level, it is difficult to satisfy the currently available equipment and methods. Therefore, the study of EMCCD readout noise calibration method under high gain is of great significance for the theoretical study of EMCCD and the design of low-noise electronics. In this paper, we propose a calibration system of "cascaded integrating sphere + parallel light pipe" local illumination in dark room environment, through which we can obtain the light source under ultra-low brightness, which solves the problem of difficult to obtain the point light source, and the method of local illumination can avoid the fatigue attenuation problem under the high-fold gain, and we also refine the noise model, and propose a "gain-noise" model, which can be used to calibrate the EMCCD readout noise. The noise model is refined and the "gain-noise" fitting method is proposed, and finally the readout noise test at high gain achieves a noise calibration result of about 0.8e@600x.
Multi-aperture optical systems provide a solution that can enhance resolution without the requirement for a large-diameter single-aperture system. However, one of the challenges of multi-aperture optical systems is the detection of the piston. The phase diversity (PD) technique can detect non-continuous co-phase errors and is often used for the detection of multi-aperture piston. The PD technique estimates the wavefront aberration of the optical imaging system and the target image by acquiring an image of the focal plane of an unknown target passing through the optical system and one or more images of known aberration (often chosen to be defocused). The PD technique is usually converted to a nonlinear optimization problem, but the optimization process may fall into local minima due to 2π piston ambiguity. Such a 2π piston ambiguity problem can be solved by using broadband light with multiple wavelengths. In this paper, a multi-wavelength phase diversity technique based on optimized grid search is used, which improves the detection range so that the piston and the final evaluation function values will be more likely to be within the correct range, and improves the solution success rate compared to the unoptimized grid search method.
According to requirements, a co-aperture design has been performed for the visible light remote sensing camera and the synthetic aperture radar, allowing the remote sensing satellite to acquire both visible light and radar images simultaneously. The front system is a two-mirror, no-focus system with a primary mirror diameter of 3 meters, serving to compress the beam. To avoid obstruction, the primary mirror is placed off-axis. The visible light component consists of an off-axis three mirror system, with the entrance pupil aligned with the exit pupil of the front system. All three mirrors are secondary mirrors with quadratic surfaces. The primary mirror size is 500mm, and the system's focal length is 7.22m. The overall ground resolution of the system reaches sub-meter level, with a full field of view measuring 0.8° × 0.03°. Optical design software ZEMAX was employed to evaluate the imaging quality within the visible light wavelength range. The results indicate that the spot size of the system is smaller than 13μm within each field of view. At the Nyquist frequency, the modulation transfer function (MTF) values for each field of view exceed 0.4, approaching the diffraction limit, showcasing good imaging quality. This design enhances the satellite's adaptability and observational capabilities, reduces the overall size of the instrument, and saves on manufacturing and launch costs.
Currently, most space-borne optical cameras have fixed focal length and depth of focus. In this case, the range within which the target can be clearly imaged has been pre-determined before launch. However, the distance of the target to the optical camera might be unknown or change very fast and therefore focus adjustment has to be carried out to obtain clear images. However, no matter which refocusing technique is used, focus adjustment might lag behind the object distance variation and depth of focus extension is a better way. Wave-front coding can be used to extend the depth of focus of incoherent imaging system but the surface profile of the phase mask could not be changed dynamically, which is not flexible for application. In this manuscript, by combing the variable curvature mirror (VCM) and coded imaging technique together, a new depth of focus extension technique is proposed. According to our previous studies, the focal plane could be quickly adjusted by changing the curvature radius of VCM. Compared with the curvature variation speed, the exposure time of the camera is quite long. Therefore, by adjusting the focal plane very fast in a wide range during the exposure through VCM, an equivalent coded optical transfer function having no null frequency points within bandwidth is generated and the image captured is uniformly blurred. After that, with the help of digital restoration, the clear image could be obtained. Because the focal plane could be adjusted through variable curvature mirror in the range of millimeter, the proposed method could be used to obtain clear images with greatly extended depth of focus.
By capturing a series of low-resolution images which have known or unknown sub-pixel displacement between each other, high resolution image could be reconstructed through algorithms such as IBP, POCS and so on. This technique mainly aims to solve the problem of aliasing effect caused by under-sampling but one problem exists. While applying sub-pixel shift based super-resolution reconstruction, point spread function is used to simulate the imaging process but usually the point spread function corresponding to the low-resolution imaging system is used, which does not match reconstruction in high-resolution grid. According to our previous researches, the wave-front coding technique could be used to realize single image amplification based super-resolution reconstruction because the point spread function corresponding to the high-resolution grid could be digitally generated in a more accurate way. In this manuscript, the rotationally symmetric wave-front coding technique and the sub-pixel shift based super-resolution imaging are combined together and there are two advantages. First, because of decrease of the magnitude of optical transfer function caused by wave-front coding, the aliasing effect in the intermediate images is reduced keeping pitch size unchanged. Second, while doing the reconstruction in high-resolution grid, the computed point spread function corresponding to the high-resolution grid is used, which better matches the high-resolution grid. The numerical results demonstrate that better image could be obtained by incorporating rotationally symmetric wave-front coding into sub-pixel shift based super-resolution imaging.
Phase diversity technique (PD) can jointly estimate the wavefront aberration and the target image of an optical imaging system. The PD technique reconstructs images by acquiring a focal plane image of optical system and one or more images with known aberrations (often selected defocus). Due to the simple construction of the optical system, the ability to detect discontinuous co-phase errors, and its applicability to both point sources and extended targets, The PD technique is uniquely suited for spatial target imaging applications, especially for the detection of multi-aperture piston errors. However, in a spatially low-illumination environment, Poisson noise as the main noise source of the imaging system seriously affects the accuracy of the reconstructed images. In this paper, we propose a method of phase diversity technique based on a fast Non-local Means (NLM) algorithm for reconstructing single-aperture images or multi-aperture images. For the two cases of single-aperture imaging and multi-aperture imaging with piston errors in spatial low illumination conditions, the method is used to solve the sensitivity problem of Poisson noise during image reconstruction. Numerical simulation results show that our method has significant improvement in structural similarity of the recovered images compared with the traditional phase diversity technique, and also is faster than the common non-local mean algorithm. The combination of this fast non-local means algorithm which using integral images and the phase diversity technique greatly reduce the computation time. The field experimental results and simulation results show good agreement. The new method would be useful in the AO system with active Poisson noise.
In terms of optical requirements and launch costs, large-diameter mirror should not only ensure fine surface accuracy, but also pursue high the rate of lightweight. Starting with material selection and shape design, the structure design of the 2 m mirror of a space remote sensor is carried out, and the preliminary mirror body is obtained. Then, combined with a platform of design optimization called Isight that integrated modeling software, finite element analysis software, data processing and analysis software, we optimized the key structural parameters of the mirror in detail, obtained a SiC mirror with the mass of 178 kg, its the rate of lightweight was as high as 90.9% and the RMS of surface shape accuracy under gravity deformation is 2.2 nm. On this basis, we designed and simulated the flexible support and other mirror components. The results indicated that the first-order natural frequency of the mirror components was 113.8 Hz, the RMS of surface shape accuracy was 8.1 nm under gravity deformation when the optical axis is horizontal, and 8.2 nm under the condition of 2°C temperature change, which were better than λ/60, could meet the requirement of the design index completely.
The classical Preston equation considers that the material removal is linearly related to time, velocity, and pressure. However, in the wheel polishing technology, it is found through experiments that there is a nonlinear relationship between the rotational speed of the polishing wheel and the amount of material removed. In order to accurately control the material removal in the polishing wheel variable speed machining strategy, it is necessary to modify the classical Preston equation. In this paper, the control variable method is used to carry out the sampling experiment: the time and pressure are set as fixed values, and the polishing wheel speed is set as a variable and the value is between 0-4rps. Then the data points were analyzed and a least squares fit was used to obtain a non-linear function between the rotational speed of the polishing wheel and the amount of material removed. Finally, the classical Preston equation is modified to obtain the removal equation suitable for the variable speed machining strategy.
It is difficult for normal CCD or CMOS camera to obtain high quality images under extremely low-light conditions for example the new moon or the quarter moon because the photons arriving at the detector are so few that signal to noise ratio (SNR) is much lower than what is necessary to resolve finer details in the nighttime scenario. To solve this problem, the intensified CCD or CMOS camera is adopted and the few photons is amplified to improve the SNR a lot. However, the intensifier is mainly composed of the cathode, MCP (Micro-channel-plate) and fluorescent screen and this complex structure and the multiple photoelectric conversion during the photon amplification process will lead to a big equivalent pitch size, which degrades the spatial resolution. Therefore in this manuscript, by improving the classical iterative back projection (IBP) algorithm a super-resolution reconstruction algorithm is proposed. By fusing multiple quite noisy lowlight images having sub-pixel displacements between each other, both the spatial resolution and the SNR could be enhanced. In the in-lab experiments, the spatial resolution can be increased to nearly 1.8 times the original one. Besides that, the increment in SNR bigger than 6dB and 9dB could be obtained for the quarter moon and the new moon light condition respectively. The out-door experiments show the similar results and besides that by fusing sub-pixel shifted low-light images corresponding to different low-light conditions together, the reconstructed high-resolution images will have even better visual performance.
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