关键词: 合成孔径雷达, 相干斑噪声抑制, 各向异性扩散, 匀质性测度, 鲁棒统计量

Abstract:

Current speckle reduction anisotropic diffusion algorithms cannot adequately smooth the speckle noise in homogeneous areas and make the edges blurred as the number of iteration increases. A novel speckle reduction anisotropic diffusion algorithm is proposed in this paper based on information-theoretic heterogeneity measurement which can effectively discriminate the homogeneous area and the edge area. With this useful property of the information-theoretic heterogeneity measurement, the diffusion coefficient can better control the diffusion strength and the speed to fully suppress the speckle noise and meanwhile preserve the edges. Based on the equivalence of solving the anisotropic diffusion equation and minimizing the robust error norm, a stopping iteration criterion is designed for the anisotropic diffusion equation. Synthetically speckled and real synthetic aperture radar images are utilized to test the smoothing performance and the ability to preserve edges of the proposed algorithm, and the experimental results show its efficiency and superiority over the traditional algorithms.

Key words: synthetic aperture radar, speckle noise suppression, anisotropic diffusion, heterogeneity measurement, robust statistics