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9 October 2018 Artefact suppression in multispectral images degraded by motion blur and restored by Wiener filtering
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Abstract
In this presentation, we deal with the design of a filter based on the geodesic distance affinity which can able to suppress the low frequency artifacts as a post-processing step after the main Winner filter restoration. We consider the multispectral signal model in the case of the Winner filter restoration independently in each image channel. The impulse response of the obtained filter is a linear combination of generalized filters optimized with respect to different criteria. The main idea of the proposed algorithm is based on assumption that low frequency outliers and the additional noise in the different image channels are not correlate to each other, thus the affinity space formed by of the opposite channels can effectively suppress the main restoration artifacts. The performance of the proposed filter analyzed and compared in terms of the PSNR accuracy. The proposed method demonstrates the ability to suppress distortion due to the low frequency artifacts.
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Victor N. Karnaukhov and Mikhail G. Mozerov "Artefact suppression in multispectral images degraded by motion blur and restored by Wiener filtering", Proc. SPIE 10789, Image and Signal Processing for Remote Sensing XXIV, 107891H (9 October 2018); https://doi.org/10.1117/12.2325246
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