A Non-Local despeckling approach using pixel-similarity thresholding
| Autor: | Tan Xiaomin, He Yapeng, Li Guangting, Dang Hongxing |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Similarity (geometry)
Pixel Physics::Instrumentation and Detectors business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Probability density function Pattern recognition Function (mathematics) Texture (music) Thresholding Measure (mathematics) Image (mathematics) Computer Science::Computer Vision and Pattern Recognition Artificial intelligence business Mathematics |
| Zdroj: | IET International Radar Conference 2013. |
| DOI: | 10.1049/cp.2013.0210 |
| Popis: | We propose a Non-Local despeckling approach by using the new pixel-relativity measure, based on ratio distance, and thresholding the pixel-similarity. Firstly, the pixel-relativity model based on ratio distance is obtained by transforming the joint probability density function of two pixels having the same reflectivity. Then a table of pixel-similarity threshold, as a function of the SAR image look number and neighboring reflectivity ratio, is trained according to the minimum error probability criterion. Finally, the pixel-similarity threshold is used to select similar pixels from the searching window for real reflectivity estimation. The proposed approach is verified by the comparison with PPB and LHRS-PRM filters using synthetic and real SAR images. The visual quality and the quantification comparison show that our method is excellent in restoring not only the uniform area but also the borders and texture area. (6 pages) |
| Databáze: | OpenAIRE |
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