Image Denoising Based on Support Vector Machine
| Autor: | Guo-Duo Zhang, Xu-Hong Yang, Hang Xu, Dong-Qing Lu, Yong-Xiao Liu |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
business.industry
Noise reduction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Non-local means Support vector machine Computer Science::Computer Vision and Pattern Recognition Image noise Median filter Video denoising Computer vision Artificial intelligence business Image restoration Mathematics Feature detection (computer vision) |
| Zdroj: | 2012 Spring Congress on Engineering and Technology. |
| DOI: | 10.1109/scet.2012.6341928 |
| Popis: | Image in the collection, transmission and other processes, often affected to some extent, resulting in noise. The purpose of image denoising is obtained from the degraded image noise removal, restore the original image. Traditional denoising methods can filter noise, but at the same time they make the image details fuzzy. The support vector machine based method for image denoising is a good method，thus it can not only wipe of noise, but also retain the image detail. Support vector machine is a machine learning, which based on statistical learning theory, and this method is widely applied to solve classification problems. This paper proposes an image denoising method based on support vector regression; also this paper describes several other methods of image denoising. Simulation results show that the method can save the image detail better, restore the original image and remove noise. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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