Artifact Suppression with Geodesic Kernel Filter for Defocused Images Restored by Wiener Filtering

Abstract—The Wiener-filter restoration of images degraded by defocus blur usually causes specific low frequency artifacts. In this work, we propose to suppress such low frequency artifacts with a filter based on the geodesic distance affinity. A multispectral signal model is considered and the main idea of the proposed algorithm is based on assumption that low frequency outliers and additive noise in different image channels are uncorrelated. Thus, the affinity space formed by opposite channels can be used to efficiently suppress the Wiener filter restoration artifacts. The performance of the proposed filter is analyzed and compared in terms of the PSNR accuracy.

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