The Optimal (m,n) Fuzzy Rank Order Filter with Neural Learning

• Main Authors: Chang, Ja-Shan, 張介相
• Other Authors: Yu, Pao Ta
• Format: Others
• Language: en_US
• Published: 1994
• Online Access: http://ndltd.ncl.edu.tw/handle/59241028867555409718

碩士 === 國立中正大學 === 資訊工程研究所 === 82 === Stack filters are nonlinear filters which are based on positive Boolean functions as their window operators. Each positive Boolean function gives distinct effect on the image. First, we define two new filters that are called (m, n) rank order filters and (m, n) fuzzy rank order filters where m<n. We set a counter to count the number of 1s for any input signal of window width 2N+1. If the counter has more than n, then the output is 1. If the counter has less than m, then the output is 0.The difference of (m, n) rank order filters and (m, n) fuzzy rank order filters is at the value of the output when the counter is between m and n. For (m, n) rank order filters, we still take 0 or 1 as the output when the counter is between m and n. But we take a continue value between 0 and 1 as the output for (m, n) fuzzy rank order filters when the counter is between m and n. In this algorithm, We propose the cube membership function. And we adjust the shape of the cube membership function by neural learning. From those, we can find an optimal (m, n) fuzzy rank order filter. Finally, we also can get the optimal stack filter.