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Contrast enhancement and denoising of Poisson and Gaussian mixture noise for solar images

Begovic, B. and Stankovic, V. and Stankovic, L. (2011) Contrast enhancement and denoising of Poisson and Gaussian mixture noise for solar images. In: Proceedings of the 18th IEEE International Conference on Image Processing (ICIP). IEEE, New York, pp. 185-188. ISBN 9781457713040

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Processing of solar image data has become increasingly important for accurate space weather prediction and expanding our understanding about the Sun and Universe. To enable proper analysis, image denoising and contrast enhancement are essential for removal of all artifacts introduced within the acquisition process. Hence, this paper focuses on these two tasks applied on solar images corrupted with pixel dependent Poisson and zero-mean additive Gaussian noise. The denoising frameworks are build upon on two state-of-the-art techniques, K-SVD and BM3D (for natural images) where contrast enhancement of noisy solar images is performed jointly with noise removal using sparse coding adaptive dictionary learning. Results are given for two conventional sets of solar images.