Switching Median Filter, Extremum Median Filter, Adaptive Median Filter - MATLAB Implementation

The code package includes M-file source code implementations for switching median filter, extremum median filter, and adaptive median filter algorithms. The switching median filter is a commonly used image filtering algorithm that removes noise by sorting image pixels and calculating median values within specified neighborhoods. The implementation typically involves pixel value sorting using MATLAB's sort function and conditional replacement based on noise detection thresholds. The extremum median filter is an image filtering method based on pixel extreme points, which achieves image smoothing by detecting extreme value points and performing median calculations. This algorithm often utilizes neighborhood analysis to identify outlier pixels before applying median filtering specifically to those regions. The adaptive median filter is an advanced filtering algorithm that dynamically adjusts the filter size according to the characteristics of the pixel's surrounding neighborhood. This approach effectively removes noise at different scales by progressively increasing the window size until optimal filtering conditions are met. The MATLAB implementation typically involves iterative window expansion and statistical analysis of local pixel distributions. These M-file source codes provide practical implementations that can help achieve image processing results similar to those described in research papers, with proper parameter tuning and neighborhood configuration.