Speckle Denoising for Synthetic Aperture Radar Images Based on Genetic Algorithm and 2D Dual-Tree Complex Wavelet Transform (2D-DT-CWT)

Abstract

Synthetic aperture radar (SAR) images are an important tool for obtaining target information in remote sensing. Synthetic aperture radar (SAR) images are inherently affected by multiplicative speckle noise, which is due to the coherent nature of the scattering phenomenon. It appears sensible to reduce speckle in SAR images, provided that the structural features and textural information are not lost. Present A novel speckle removal algorithm is presented by using Dual-Tree Complex Wavelet Transform (2D-DT-CWT) and Genetic algorithm (GA). In the proposed model, Genetic algorithm based on 2D Dual-Tree Complex Wavelet Transform is introduced into the method of noise reduction where parameters used in Dual-Tree Complex Wavelet Transform, such as, decomposition levels, hard or soft threshold and threshold value can be selected automatically. Simulation results show that by using proposed method, obtain higher Peak Signal to Noise Ratio (PSNR) comparing with classical wavelet transform for all the denoised SAR images with speckle noise. The effectiveness of proposed method introduced in this paper is validated by the results of analysis of the simulated.