Traditional Methods in Image Processing - Median Filtering

One of the traditional methods in image processing is median filtering. Median filtering is a widely-used image processing technique that effectively removes noise from images while improving overall image quality. The core principle involves replacing each pixel's gray value with the median value of the gray values in its surrounding neighborhood. This method effectively smoothens images while preserving edge information, making median filtering particularly valuable for applications requiring noise reduction, edge preservation, and image enhancement in digital image processing. In practical implementation, median filtering typically operates by sliding a window (usually 3×3 or 5×5 pixels) across the image. For each pixel position, the algorithm collects all pixel values within the window, sorts them in ascending order, and selects the median value as the new pixel value. This non-linear filtering approach proves especially effective against salt-and-pepper noise while maintaining sharp edges better than linear filters. The key implementation steps involve neighborhood pixel collection, quick sort algorithms for median calculation, and boundary case handling for image edges.