De-noising of SAR images based on Wavelet-Contourlet domain and PCA

After analyzing the speckle model of SAR, a SAR image de-noising method based on Wavelet-Contourlet transform and principal component analysis is presented. Compared with Wavelet transform and Contourlet transform, Wavelet-Contourlet transform can express images more sparsely and obtain image structure better. Most of the existing methods for image de-noising rely on accurate estimation of noise variance. However, the estimation of noise variance is very difficult in Wavelet-Contourlet domain. Propose a new method for SAR image de-noising based on Wavelet-Contourlet transform and principal component analysis. Simulation results also corroborate that the proposed algorithm is efficient and performs significantly better in reducing the speckle noise, obtaining a higher peak signal-to-noise ratio, retaining the image details, and improving the visual effect.

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