Poisson Denoising for Astronomical Images
A denoising scheme for astronomical color images/videos corrupted with Poisson noise is proposed. The scheme employs the concept of Exponential Principal Component Analysis and sparsity of image patches. The color space RGB is converted to YCbCr and K-means++ clustering is applied on luminance compo...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
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| Series: | Advances in Astronomy |
| Online Access: | http://dx.doi.org/10.1155/2018/2417939 |
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| Summary: | A denoising scheme for astronomical color images/videos corrupted with Poisson noise is proposed. The scheme employs the concept of Exponential Principal Component Analysis and sparsity of image patches. The color space RGB is converted to YCbCr and K-means++ clustering is applied on luminance component only. The cluster centers are used for chromatic components to improve the computational efficiency. For videos, the information of both spatial and temporal correlations improves the denoising. Simulation results verify the significance of proposed scheme in both visual and quantitative manner. |
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| ISSN: | 1687-7969 1687-7977 |