A Novel Speckle Suppression Method with Quantitative Combination of Total Variation and Anisotropic Diffusion PDE Model

• Published in: Remote sensing (Basel, Switzerland) Vol. 14; no. 3; p. 796
• Main Authors: Li, Jiamu, Wang, Zijian, Yu, Wenbo, Luo, Yunhua, Yu, Zhongjun
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.02.2022
• Subjects: Anisotropy; Antennas; Coefficient of variation; Diffusion; Diffusion coefficient; Edge detection; Methods; Noise; Noise levels; partial differential equation; Partial differential equations; Propagation; quantifiable pixel position; Radar imaging; speckle suppression; Synthetic aperture radar; synthetic aperture radar image; total variation; Variation
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs14030796

Speckle noise seriously affects synthetic aperture radar (SAR) image application. Speckle suppression aims to smooth the homogenous region while preserving edge and texture in the image. A novel speckle suppression method based on the combination of total variation and partial differential equation denoising models is proposed in this paper. Taking full account of the local statistics in the image, a quantization technique—which is different from the normal edge detection method—is supported by the variation coefficient of the image. Accordingly, a quantizer is designed to respond to both noise level and edge strength. This quantizer automatically determines the threshold of diffusion coefficient and controls the weight between total variation filter and anisotropic diffusion partial differential equation filter. A series of experiments are conducted to test the performance of the quantizer and proposed filter. Extensive experimental results have demonstrated the superiority of the proposed method with both synthetic images and natural SAR images.