Wavelet-based multiscale anisotropic diffusion for speckle reduction and edge enhancement
Yi Wang, Ruiqing Niu, Ke Wu, Xin Feng Yu · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2009
In order to improve signal-to-noise ratio (SNR) and image quality, this paper introduces a wavelet-based multiscale anisotropic diffusion algorithm to remove speckle noise and enhance edges. In our algorithm, we use the tool of wavelet to construct a linear scale-space for the speckle image. Due to the smoothing functionality of the scaling function, the wavelet-based multiscale representation of the speckle image is much more stationary than the raw speckle image. Noise is mostly located in the finest scale and tends to decrease as the scale increases. Furthermore, a robust speckle reduction anisotropic diffusion (SRAD) is to be proposed and we perform the improved SRAD on the stationary scale-space rather than on the rough speckle image domain. Qualitative experiments based on a speckle Synthetic aperture radar (SAR) image show the elegant characteristics of edge-preserving filtering versus the traditional adaptive filters. Quantitative analyses, based on the first order statistics and Equivalent Number of Looks, confirm the validity and effectiveness of the proposed algorithm.