New Morphological Filtering Algorithm for Image Noise Reduction
Cheng Huang, Youlian Zhu · 2009
Conventional morphological filter is disabling to effectively preserve image details while removing noises from an image. The proposed algorithm of the self adaptive median morphological filter is implemented as follows. First, the extreme value operation is displaced by the median operation in erosion and dilation. Then, the structuring element unit (SEU) is built based on the zero square matrix. Finally, the peak signal to noise ratio (PSNR) is used as the estimation function to select the size of the structuring element. Simulation results show that the proposed filter can effectively resolve the problem between detail-preserving and noise-removing, and its performance is obviously superior to others especially in the low signal to noise ratio situation. When the noise density is 75%, its PSNR is higher 11-14 dB than the conventional morphological filter and 10-12 dB than the median filter.