Pixel Difference Function and Local Entropy-Based Speckle Reducing Anisotropic Diffusion

Abstract

Speckles destroy the texture details of synthetic aperture radar (SAR) images, thereby constraining their high-precision application. Speckle suppression and edge preservation are two aspects that need to be balanced in despeckling. Although a conventional anisotropic diffusion filter can theoretically achieve this balance, it still triggers many edge losses. To better improve the balance, a novel anisotropic diffusion (AD) filter based on the pixel difference function and local entropy is proposed. The proposed filter utilizes a pixel difference function to update the original diffusion function of the AD filter and introduces local entropy to recover the edge loss from the ratio image generated by noisy and filtered images. In addition, a neighborhood weighting approach and a new adaptive iterative rule are proposed for better AD filtering. Simulated data and real SAR images were applied to evaluate the performance of the proposed algorithm. Experimental results show that the proposed filter both effectively smooths speckles and reduces edge loss. Furthermore, the effectiveness and superiority of the proposed method were confirmed by comparison with other state-of-the-art methods.