Enhancement of contrast in digital speckle pattern interferometry fringes using wavelet transform

Abstract

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.