Two ICA Approaches for SAR Image Enhancement
Chi Hau Chen, Xianju Wang, Salim Chitroub · 2006
CONTENTS 20.1 Part 1: Subspace Approach of Speckle Reduction in SAR Images Using ICA..... 441 20.1.1 Introduction ....................................................................................................... 441 20.1.2 Review of Speckle Reduction Techniques in SAR Images ........................ 442 20.1.3 The Subspace Approach to ICA Speckle Reduction................................... 442 20.1.3.1 Estimating ICA Bases from the Image ......................................... 442 20.1.3.2 Basis Image Classification .............................................................. 442 20.1.3.3 Feature Emphasis by Generalized Adaptive Gain..................... 444 20.1.3.4 Nonlinear Filtering for Each Component .................................... 445 20.2 Part 2: A Bayesian Approach to ICA of SAR Images............................................... 446 20.2.1 Introduction ....................................................................................................... 446 20.2.2 Model and Statistics ......................................................................................... 447 20.2.3 Whitening Phase ............................................................................................... 447 20.2.4 ICA of SAR Images by Ensemble Learning ................................................. 449 20.2.5 Experimental Results........................................................................................ 451 20.2.6 Conclusions........................................................................................................ 452 References ................................................................................................................................... 454 20.1.1 Introduction The use of synthetic aperture radar (SAR) can provide images with good details under many environmental conditions. However, the main disadvantage of SAR imagery is the poor quality of images, which are degraded by multiplicative speckle noise. SAR image speckle noise appears to be randomly granular and results from phase variations of radar waves from unit reflectors within a resolution cell. Its existence is undesirable because it degrades quality of the image and affects the task of human interpretation and evaluation. Thus, speckle removal is a key preprocessing step for automatic interpretation of SAR images. A subspace method using independent component analysis (ICA) for speckle reduction is presented here.