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本源码是利用Sparse Prior复原图像的方法,其中包括频域和空域的复原比较,源码中有相应的文章Deconvolution using natural image priors-Deconvolution using natural image priors
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图像去噪-A Generative Perspective on MRFs in Low-Level Vision-A Generative Perspective on MRFs in Low-Level Vision
Markov random fields (MRFs) are popular and generic
probabilistic models of prior knowledge in low-level vision.
Yet their generative
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Bayesian Deblurring with Integrated Noise Estimation-Bayesian Deblurring with Integrated Noise Estimation
Conventional non-blind image deblurring algorithms
involve natural image priors and maximum a-posteriori
(MAP) estimation. As a consequenc
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应用于超分辨成像; 图像处理; 图像重建;图像恢复(Deconvolution using natural image priors Gaussian Prior Deconvolution)
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The sky region of restored images often appears serious noise and color distortion using classical dark channel prior algorithm. To address this is- sue, we propose an improved dark channel prior algorithm which recognizes the sky regions in hazy ima
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An important aim of research on the blind image
quality assessment (IQA) problem is to devise perceptual models
that can predict the quality of distorted images with as little
prior knowledge of the images or their distortions as possible.
Curren
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