Adaptive Median Filter

In MATLAB 6.5.1, we can utilize the adpmedian.m function to implement adaptive median filtering. This sophisticated image processing technique dynamically adjusts filter parameters based on local image characteristics, providing superior noise removal compared to standard median filters. The algorithm works by examining pixel neighborhoods at multiple scales, automatically selecting the optimal window size to preserve edges while effectively eliminating salt-and-pepper noise and other artifacts. The adpmedian.m function implements a progressive filtering approach where it initially applies a small kernel size and progressively increases the window dimensions until either noise is removed or a maximum specified size is reached. Key implementation features include adaptive threshold calculation, dynamic window resizing, and edge preservation mechanisms. By employing the adpmedian.m function, users can perform sophisticated adaptive median filtering on images according to specific requirements, resulting in clearer and more accurate image outputs with minimized distortion of important features and textures. The function handles various noise types and maintains image integrity through intelligent parameter adjustment throughout the filtering process.