Two Support Vector Machine Methods for Image Noise Filter

Zekun Wang, Fuxi Zhang

Abstract


To solve the fatal limitation of SVMs based on the pre-known, two new image noise filter methods - Support Vector Machine based on self-learning machine (SLM-SVM) were presented, which is working better than many other non-linear filters, such as median filters and adaptive filters. A series of comparison and working parameters would be explained, performance of test showed these methods can dealing with the noise in a totally unknown image. And filter out more than 99% noise pixels from an image. In the same time, this kind of filter is still immature due to its long runtime (more than 2 second) and some error cases during testing, some recommendation and prediction were proposed.


DOI
10.12783/dtmse/ameme2020/35558

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