SAR Clutter Statistical Modeling Source Code

The source code developed for SAR clutter statistical modeling in this project serves dual purposes: it provides essential data sources for SAR image denoising operations and functions as a highly effective tool for investigating SAR image segmentation techniques. The codebase implements key statistical models including K-distribution, Gamma distribution, and Weibull distribution fitting algorithms with maximum likelihood estimation methods. Through utilizing these source programs, researchers can perform more accurate denoising processing on SAR images and obtain precise auxiliary tools for segmentation analysis. The implementation features modular functions for parameter estimation, probability density function calculation, and goodness-of-fit testing. These programs hold significant importance in the field of SAR image processing and analysis, providing substantial data and tool support for related research endeavors, including adaptive thresholding algorithms and region-based segmentation approaches.