MATLAB Code Implementation of Median Filter for Noise Reduction

In digital image processing, we can implement a median filter using MATLAB to effectively eliminate pepper and salt noise. The median filter operates by replacing each pixel's value with the median value of its neighboring pixels within a specified window size, typically using a sliding window approach. This non-linear filtering technique is particularly effective for impulse noise like pepper and salt noise while preserving image edges better than linear filters.

Key implementation aspects include using MATLAB's medfilt2 function for 2D median filtering, where you specify the window dimensions (e.g., [3 3] for a 3x3 neighborhood). The algorithm processes each pixel by extracting its neighborhood, sorting the pixel values, and selecting the median value. For color images, the filter can be applied separately to each RGB channel. Proper window size selection is crucial - smaller windows preserve details but may not remove all noise, while larger windows provide better noise removal but might blur fine details.

The median filter's effectiveness stems from its ability to ignore extreme values (typical of pepper and salt noise) when calculating the median, making it superior to mean filters for this specific noise type. Implementation typically involves handling image borders using padding techniques like symmetric or replicate padding to maintain image dimensions.