Speckle Noise Reduction in Satellite Images Using Spatially Adaptive Wavelet Thresholding

This paper presents an efficient algorithm for removing noise in satellite images by combining Wavelet Thresholding, Total Variation in wavelet domain and Bilateral Filter, Joint Bilateral Filter (JBF) in spatial domain. During the first stage, the noisy image is passed through Bilateral Filter(BF) and some amount of noise is reduced but the image becomes blurred, hence adaptive wavelet thresholding is applied while applying the threshold rule, the important features in an image such as edges, curves and textures can be identified. In the third stage, Total Variation (TV) method is applied to wavelet threshold output denoised image. Also spatial domain method output provides a high quality denoising image than wavelet method with less artifacts, hence this wavelet domain output as a reference image for the Joint Bilateral Filter (JBF) .With the help of this reference image in the final stage and the non-linear combination of information of adjacent pixel, the edge details of the images can be preserved in a well manner. The experimental results prove that the proposed approach is competitive when compared to other denoising methods in reducing various types of noise. Also the proposed algorithm outperforms other methods both visually and in case of objective quality peak-signal-to-noise ratio (PSNR).The method also retains the edges and other detailed information very well. Keywords— Image Restoration; Dyadic Wavelet Transform;Multiscale product Wavelet Thresholding;Joint Bilateral Filter.