Joint Color Space GMMs for CFA Demosaicking
| Autor: | P. Sandeep, Tony Jacob |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Demosaicing
Pixel Computer science business.industry Color image Applied Mathematics Gaussian ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020206 networking & telecommunications Pattern recognition 02 engineering and technology Color space symbols.namesake Computer Science::Computer Vision and Pattern Recognition Color gel Signal Processing 0202 electrical engineering electronic engineering information engineering symbols Artificial intelligence Electrical and Electronic Engineering business Interpolation |
| Zdroj: | IEEE Signal Processing Letters. 26:232-236 |
| ISSN: | 1558-2361 1070-9908 |
| DOI: | 10.1109/lsp.2018.2886466 |
| Popis: | We propose a patch-based algorithm for demosaicking a mosaicked color image produced by color filter arrays commonly used in acquiring color images. The proposed algorithm exploits a joint color space Gaussian mixture model (JCS-GMM) prior for jointly characterizing the patches from red, green, and blue channels of a color image. The inter channel correlations captured by the covariance matrices of Gaussian models are exploited to estimate the pixel values missing in the mosaicked image. The proposed JCS-GMM demosaicking algorithm can be seen as the GMM analogue of the Color-KSVD algorithm, which has produced impressive results in color image denoising and demosaicking. We demonstrate that our proposed algorithm achieves superior performance in the case of Kodak and Laurent Condat's databases, and competitive performance in the case of IMAX database, when compared with state-of-the-art demosaicking algorithms. |
| Databáze: | OpenAIRE |
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