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- W4386907160 abstract "A noise-corrupted image often requires interpolation. Given a linear denoiser and a linear interpolator, when should the operations be independently executed in separate steps, and when should they be combined and jointly optimized? We study joint denoising / interpolation of images from a mixed graph filtering perspective: we model denoising using an undirected graph, and interpolation using a directed graph. We first prove that, under mild conditions, a linear denoiser is a solution graph filter to a maximum a posteriori (MAP) problem regularized using an undirected graph smoothness prior, while a linear interpolator is a solution to a MAP problem regularized using a directed graph smoothness prior. Next, we study two variants of the joint interpolation / denoising problem: a graph-based denoiser followed by an interpolator has an optimal separable solution, while an interpolator followed by a denoiser has an optimal non-separable solution. Experiments show that our joint denoising / interpolation method outperformed separate approaches noticeably." @default.
- W4386907160 created "2023-09-21" @default.
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- W4386907160 date "2023-09-18" @default.
- W4386907160 modified "2023-09-27" @default.
- W4386907160 title "Mixed Graph Signal Analysis of Joint Image Denoising / Interpolation" @default.
- W4386907160 doi "https://doi.org/10.48550/arxiv.2309.10114" @default.
- W4386907160 hasPublicationYear "2023" @default.
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