Speckle noise suppression in SAR images (Oil spill images) using wavelet based methods and ICA technique
M Bharaneswari, Pachiyappan Arulmozhivarman, Rao Tatavarti, Krishnamoorthy Senthilnathan · 2015
Synthetic Aperture Radar (SAR) images are inherently degraded due to the coherent nature of the scattering phenomena called speckle. The presence of speckle decreases the utility of the SAR images by reducing the ability to detect ground objects. It affects the quality of the image adversely and hampers the observation of vital and crucial information present in the image. In this paper, we present speckle noise suppression techniques using wavelet decomposition and ICA methods. The algorithms viz., Projection Onto Approximation Coefficients (POAC), Projection Onto Span Algorithm (POSA) and Independent Component Analysis (ICA) are implemented on real SAR images and their results are tabulated. A comparison is made with standard speckle filters such as Lee filter, Frost filters, etc. The performance of our methods is measured in terms of Peak Signal-to-Noise Ratio (PSNR) values.