Speckle Reduction Using Fuzzy Morphological Anisotropic Diffusion

Abstract

One of important tasks of radar image processing is reducing speckle noise as preprocessing to enhance performance of other processing such as segmentation, classification, etc. In this paper, we then apply the fuzzy morphology together with anisotropic diffusion to reduce speckled noise of SAR image. Anisotropic diffusion is designed based on additive noise model, but the form of speckled image is in multiplicative speckle model. To transform additive noise model into multiplicative speckle model, logarithmic transformation is then used. Our algorithm performs in log-domain. Finally, de-speckled image being in log-domain is converted into spatial domain by using exponential transformation. Simulated image as speckled image is performed with our algorithm to show and compare results with recent reports in term of both signal to noise ratio (SNR) and the equivalent number of looks (ENL). Also, real SAR image is performed to confirm results in term of ENL only. Results from our experiment are shown that de-speckled image can smooth out in homogeneous area and preserve edge in heterogeneous area. Both visual image and numerical results are used to show all results