Lee Filter Implementation for Coherent Speckle Noise Reduction Algorithm

In Synthetic Aperture Radar (SAR) image processing, the Lee filter algorithm is a commonly used method for coherent speckle noise reduction. The algorithm operates by estimating the local mean and variance within each pixel's neighborhood, then calculating corresponding filter coefficients to achieve denoising. A typical implementation involves sliding a window through the image matrix, computing statistical measures for each window position, and applying the Lee filter equation: filtered_value = mean + K*(original_value - mean), where K depends on the local variance-to-mean ratio. The primary advantage of the Lee filter algorithm lies in its ability to effectively remove noise from SAR images while preserving image detail information. Consequently, in SAR image processing applications, the Lee filter algorithm has gained widespread adoption as a crucial image denoising technique, particularly valuable for maintaining edge sharpness and texture features during noise suppression.