Similarity based Anisotropic Diffusion Filter
| Autor: | Ufuk Tanyeri, Recep Demirci, Mursel Ozan Incetas |
|---|---|
| Přispěvatelé: | Zonguldak Bülent Ecevit Üniversitesi |
| Jazyk: | turečtina |
| Rok vydání: | 2016 |
| Předmět: |
Pixel
Anisotropic diffusion business.industry Diffusion filter ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020206 networking & telecommunications 02 engineering and technology Edge-preserving smoothing Non-local means Noise anisotropic diffusion filter Computer Science::Computer Vision and Pattern Recognition 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Bilateral filter Artificial intelligence Diffusion (business) similiarity coefficent business Algorithm Mathematics |
| Zdroj: | SIU |
| Popis: | 24th Signal Processing and Communication Application Conference (SIU) -- MAY 16-19, 2016 -- Zonguldak, TURKEY WOS: 000391250900327 Different filter methods to reduce noises occurred during image capture have been developed. One of the most effective image filters is diffusion filter. However, the major drawback of conventional diffusion filter is user-dependent. While noises are reduced with conductance coefficient arbitrarily selected, edge pixels are perceived such as noise. In this study, a novel anisotropic diffusion filter using similarity values obtained with the distance of each pixel to its neighbors has been proposed. Initially, similarity values of all image pixels are computed, and then they are used as conductance coefficients in diffusion filter. The mentioned value above is user dependent for conventional diffusion and it is constant for all pixels. On the other hand, it is made adaptive and eliminated user intervention with suggested approach. Developed method has been tested with different noise variances of images and experimental results have been compared with conventional diffusion filter. IEEE, Bulent Ecevit Univ, Dept Elect & Elect Engn, Bulent Ecevit Univ, Dept Biomed Engn, Bulent Ecevit Univ, Dept Comp Engn |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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