In patch-based denoising techniques, the input noisy image is divided into patches (i.e., blocks). The blocks are then manipulated separately in order to provide an estimate of the true pixel values.
Aug 24, 2017
Oct 19, 2011 · Abstract: In this paper, we propose a denoising method motivated by our previous analysis of the performance bounds for image denoising.
This paper proposes a patch-based Wiener filter that exploits patch redundancy for image denoising that is on par or exceeding the current state of the art, ...
Our denoising approach, designed for near-optimal performance (in the mean-squared error sense), has a sound statistical foundation that is analyzed in detail.
Our denoising approach, designed for near-optimal performance (in the mean-squared error sense), has a sound statistical foundation that is analyzed in detail.
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Abstract—In this paper, we propose a denoising method motivated by our previous analysis [1], [2] of the performance bounds for image denoising.
We propose a patch-based Wiener filter that exploits patch redundancy for image denoising. Our framework uses both geometrically and photometrically similar ...
Jan 18, 2019 · We present a patch searching method that clusters similar patch candidates into patch groups using Gaussian Mixture Model-based clustering.
ABSTRACT. In our previous work [1], we formulated the fundamental lim- its of image denoising. In this paper, we propose a practical.
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We focus on improving the denoising performance by the means of finding reliable candidate sets. We express patch-based locally optimal wiener (PLOW) ...