Nonlocal patch-based method on spatially-variant amoeba morphology for image restoration
| Autor: | Shuo Yang, Jianxun Li |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Pixel
Kernel (image processing) Noise (signal processing) Structuring element Computer science Amoeba (mathematics) Boundary (topology) Electrical and Electronic Engineering Algorithm Atomic and Molecular Physics and Optics Image restoration Quantitative Biology::Cell Behavior Electronic Optical and Magnetic Materials |
| Zdroj: | Optik. 126:283-288 |
| ISSN: | 0030-4026 |
| DOI: | 10.1016/j.ijleo.2014.08.164 |
| Popis: | In view of the selection of structuring elements problem in morphological filters, this paper presents a new method to generate structuring elements for spatially-variant morphology. This method takes the theory of amoeba morphology as a foundation and new amoeba distances to generate structuring elements for spatially-variant filters are defined. The proposed strategy essentially consists in an amoeba kernel is divided into two parts: one is the patch-based center; another is the pixel-based boundary, the two parts combining both nonlocal patch-based distance and local pixel-based distance. This nonlocal and local configurations make nonlocal patch-based processing method becomes local processing on amoeba structuring element. New amoeba kernels are less flexible at patch-based center than traditional amoebas and their shape is less affected by noises in pilot image. By designing new amoeba structuring element, a new family of morphological filters are derived that have better performance in removing the noise while adaptively preserving the main structures compared with traditional amoeba filters. |
| Databáze: | OpenAIRE |
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