SAR Image Filters: GAMMA, Lee, and Median Filtering Techniques

The original text discusses SAR image filters, specifically GAMMA, Lee, and median filters. In SAR image processing, filters play a crucial role in enhancing image quality by reducing noise and improving clarity. The GAMMA filter employs a weighted averaging approach to minimize noise impact, typically implemented using local window statistics and gamma distribution modeling. The Lee filter utilizes statistical characteristics of SAR imagery for noise suppression, often incorporating scene heterogeneity detection through coefficient calculations based on local mean and variance. Median filtering operates by replacing pixel values with the median value within a sliding kernel, making it particularly effective for removing salt-and-pepper noise in SAR images. Therefore, selecting appropriate filters is essential in SAR image processing to achieve superior results, producing clearer and more accurate imagery through proper algorithm implementation and parameter optimization.