In this paper, we propose a novel Neural Fuzzy Filter (NFF) to remove impulse noise from highly corrupted images. The proposed filter consists of a fuzzy number construction process, a neural fuzzy filtering process and an image knowledge base. First, the fuzzy number construction process will receive sample images or the noise-free image, then construct an image knowledge base for the neural fuzzy filtering process. Second, the neural fuzzy filtering process contains of a neural fuzzy mechanism, & fuzzy mean process, and a fuzzy decision process to perform the task of impulse noise removing. By the experimental results, NFF achieves better performance than the state-of-theart filters based on the criteria of Mean-Square-Error (MSB). On the subjective evaluation of those filtered images, NFF also results in a higher quality of global restoration.
|Number of pages||6|
|Journal||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Publication status||Published - 2004|
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Biochemistry, Genetics and Molecular Biology(all)
- Theoretical Computer Science