Median Filter Implementation in MATLAB

Median filtering is a commonly used image processing technique that can be efficiently implemented using MATLAB's built-in functions. The filter kernel sizes typically include 3x3, 5x5, and 7x7 configurations, with each size suitable for different image processing requirements. In MATLAB implementation, the median filter is primarily achieved using the medfilt2() function from the Image Processing Toolbox. The function syntax medfilt2(I,[m n]) applies a median filter of specified window size to image I, where m and n represent the kernel dimensions. For grayscale images, a 3x3 kernel effectively removes salt-and-pepper noise while preserving edges better than linear filters. Larger kernels like 5x5 and 7x7 provide stronger smoothing effects but may cause more detail loss. Key implementation considerations include handling image boundaries through padding options ('symmetric', 'replicate', or 'zeros') and selecting appropriate kernel sizes based on noise characteristics. The algorithm works by replacing each pixel value with the median of neighboring pixels in the defined window, making it particularly effective for impulse noise removal without blurring sharp edges as much as mean filters.