Image Median Filtering Using a 3x3 Template

This article presents a MATLAB program that employs a 3x3 template to perform median filtering on images. Median filtering is a fundamental image processing technique that effectively reduces noise while enhancing image quality. The implementation follows these computational steps: First, the target image is loaded and converted to grayscale format using MATLAB's rgb2gray() function. The algorithm then processes each pixel by applying a 3x3 neighborhood window, where the center pixel value is replaced with the median value of its surrounding eight pixels. This spatial filtering operation is implemented using nested loops to traverse all image pixels while handling boundary conditions through zero-padding or replication. The median calculation for each window is efficiently performed using MATLAB's medfilt2() function or custom sorting algorithms. Finally, the processed image is displayed using imshow() and saved to a new file with imwrite(). This MATLAB implementation provides a practical solution for image denoising and quality enhancement through median filtering techniques.