KEYWORDS: Speckle, Image filtering, Wavelets, Signal to noise ratio, Image processing, Denoising, Wavelet transforms, Digital filtering, Linear filtering, Smoothing
In automatic analysis of the time-average digital speckle interferogram, the great challenge is to get proper intensity
variation between different fringes and smoothness in the line profile of intensity distribution, so as it approaches the
governing Bessel function/map. An image processing scheme based on wavelet denoising and morphological operation
has been investigated which is very effective in reducing speckle index, width reduction of the bright fringes and in
getting proper line profile for intensity distribution. Improvement in signal to noise ratio (i.e. decrease in speckle index)
upto 28 times has been observed.
Heat input during the welding process and subsequent re-cooling changes the microstructure, hardness, toughness, and
cracking susceptibility in heat affected zone (HAZ). Weld quality of a weldment largely depends on the area of HAZ.
Determination of exact area of the HAZ by manual stereological methods and conventional visual inspection techniques
is a difficult task. These techniques of evaluation are based on approximating the complex shape of HAZ as combination
of simplified shapes such as rectangles, triangles etc. In this paper, a filtering scheme based on morphology, thresholding
and edge detection is implemented on image of weldments to assess quality of the weld. The HAZ of mild steel
specimens welded at different welding parameters by Metal Active Gas/Gas Metal Arc Welding process were compared
and presented.
Due to change in the plate constants/plate stiffness which is a function of elastic modulus, change in natural frequencies
takes place. At each natural frequency, the plate has a unique mode shape of vibration which can be easily differentiated
from mode shapes at other natural frequencies. In this paper, a technique for the evaluation of the elastic modulus is
proposed which is based on the vibration analysis of the plate using digital speckle pattern interferometry (DSPI) and
Rayleight's method. Large numbers of experiments were conducted on square aluminium plate for the boundary
condition; one edge is fixed and other edges free. The experimental result reveals that a single observation of frequency
at first torsional mode is sufficient to evaluate the elastic modulus for all practical purposes. The evaluated experimental
error was found to be less than 1%. Ease in sample preparation, simplicity in evaluation, non destructive nature of the
DSPI and speed of DSPI has good prospect to evaluate elastic modulus of a material.
KEYWORDS: Speckle, Wavelets, Signal to noise ratio, Linear filtering, Fringe analysis, Image filtering, Digital filtering, Speckle pattern, Interferometry, Optical filters
A new filtering scheme is investigated for the removal of speckle noise in the recorded fringe pattern by a digital speckle pattern interferometric technique (DSPI). The scheme consists of a preprocessing scheme i.e., averaging, sampling, thresholding, and again averaging, followed either by a symlet or biorthogonal wavelet filter. The preprocessing scheme improves the contrast between the dark and bright fringes, and the implementation of the biorthogonal wavelet filter, which is symmetrical and purely linear in phase, solves the problem of border effect and discontinuity. The developed scheme is implemented on recorded fringe patterns of a vibrating cantilever beam and vibrating square plate with all ends fixed. The performance and effectiveness of the proposed scheme in reducing speckle noise is evaluated and compared in terms of reduction in speckle index and the improvement of the signal-to-noise ratio (SNR) of speckle interferograms. The new scheme has the ability to improve the speckle index and SNR significantly.
In this paper an algorithm to measure large deformations using digital speckle pattern interferometry is presented. It facilitates recording of large number of frames and can subtract them to display speckle correlation fringes with improved signal-to-noise ratio. To further improve signal-to-noise ratio a filtering scheme is also presented by using average/median filtering followed by wavelets filtering. Experimental results and analysis are presented in detail. For a typical displacement of 200 μm, error in measurement was less than 1.5 percent. Range in measurement is governed by change in scattering property of the surface of the object.
KEYWORDS: Speckle, Digital filtering, Wavelets, Signal to noise ratio, Speckle pattern, Fringe analysis, Wavelet transforms, Interferometry, Linear filtering, Video
In this paper the study of out-of-plane or transverse vibrations in a square plate using digital speckle pattern interferometry (DSPI) is presented. To improve the accuracy of measurement, earlier we have suggested filtering scheme based on proper use of average/median filters followed by Symlet wavelet filter. In this paper we present a different filtering scheme to reduce the speckle noise and improve the accuracy of measurement of DSPI fringes by proper choice of average filter, sampling and thresholding followed by Symlet/Biorthogonal wavelet filter. The speckle index of filtered pattern is calculated and compared with speckle index of unfiltered fringe pattern. It is observed that speckle index is significantly reduced after filtering the DSPI fringe pattern. Experimentally obtained resonance frequencies for the square plate for the boundary condition fixed at all edges were compared with that of classical theory for thin plates. The resonance frequencies obtained from DSPI show good agreement with that of obtained from the classical theory.
In this paper we present a new filtering scheme for processing of DSPI fringes and implemented the same to measure the out-of-plane vibration in a rectangular plate fixed at one end and free at another end. Values of the amplitude measured by DSPI and accelerometer are in good agreement. Also mode shapes obtained from the experimental data and from the theory are almost similar.
Different methods used to reduce speckle noise in speckle correlation fringes are only partially successful. Methods based on Fourier transform, such as low pass filtering or spectral subtraction image restoration have proven to be efficient to reduce speckle noise. Fourier Method, however, does not preserve details of the object. Thus errors are introduced when filtered image pattern is used to evaluate the phase distribution. To get rid of this problem, G. H. Kauffmann and G. E. Galizzi have implemented filtering by Daubechies (db) wavelet on computer generated TV holographic fringes. But it is observed that Daubechies wavelets are not much effective at edges in the speckle fringes. Symlet wavelets are linear phase filters and are effective from center to the edges of the speckle fringes. In this paper the experimental results of speckle noise reduction to improve the contrast of the speckle correlation fringes obtained by vibrating loudspeaker diaphragm and bracket of electric motor using filtering by Symlet wavelet is presented. The results show that filtering by Symlet wavelet is quite effective to enhance the contrast of the speckle correlation fringes. A large number of experiments are conducted on surfaces having different roughness. Experimentally it was found that to achieve optimum contrast enhancement of speckle correlation fringes, lower kernel median filter followed by Symlet is required for weakly diffused surfaces and higher kernel median filter followed by Symlet is required for strongly diffused surfaces.
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