Comprehensive MATLAB Implementation of Median Filtering with Code Examples

I have developed a comprehensive median filtering program in MATLAB that implements virtually all types of median filtering techniques. This implementation includes standard fixed-window filters (with configurable kernel sizes from 3x3 to larger dimensions), weighted median filters, and adaptive median filters that automatically adjust based on local image statistics. The code features multiple boundary handling methods such as zero-padding, symmetric padding, and replication to manage edge pixels effectively. The program utilizes MATLAB's built-in medfilt2 function as a foundation while extending its capabilities with custom implementations for specialized filtering scenarios. Each filter type is implemented with optimized vectorization techniques to ensure computational efficiency when processing large images. Additionally, I have included comprehensive testing using the standard LENA benchmark image, demonstrating the program's effectiveness in noise reduction while preserving edge details. The test results showcase comparative performance between different filter types and parameter settings. This practical tool can handle various image processing tasks and achieve superior filtering results. If you're interested in median filtering techniques, I highly recommend using this program as it provides a straightforward yet powerful solution for image denoising applications. The code structure allows easy customization and integration into larger image processing pipelines.