Results 1 to 10 of about 4,040 (153)
Noise-Adaptive Non-Blind Image Deblurring
Sensors, 2022 This work addresses the problem of non-blind image deblurring for arbitrary input noise. The problem arises in the context of sensors with strong chromatic aberrations, as well as in standard cameras, in low-light and high-speed scenarios.
Michael Slutsky
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A deep variational Bayesian framework for blind image deblurring
Knowledge-Based Systems, 2022 Blind image deblurring is an important yet very challenging problem in low-level vision. Traditional optimization based methods generally formulate this task as a maximum-a-posteriori estimation or variational inference problem, whose performance highly relies on the handcraft priors for both the latent image and the blur kernel.
Qian Zhao, Hui Wang, Deyu Meng
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Effective Alternating Direction Optimization Methods for Sparsity-Constrained Blind Image Deblurring
Sensors, 2017 Single-image blind deblurring for imaging sensors in the Internet of Things (IoT) is a challenging ill-conditioned inverse problem, which requires regularization techniques to stabilize the image restoration process.
Naixue Xiong +5 more
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Overview of Blind Deblurring Methods for Single Image [PDF]
Jisuanji kexue yu tansuo, 2022 Image deblurring has been a research hotspot in computer vision and image processing for a long time. The motion blur or focus blur image caused by camera jitter, object motion or defocus will seriously affect the use and follow-up processing of the ...
LIU Liping, SUN Jian, GAO Shiyan
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Gradient-wise search strategy for blind image deblurring [PDF]
MATEC Web of Conferences, 2022 Blind image deblurring is a long-standing challenging problem to improve the sharpness of an image as a prerequisite step. Many iterative methods are widely used for the deblurring image, but care must be taken to ensure that the methods have fast ...
Wang Yunhong, Liu Dan
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Blind Deblurring Based on a Single Luminance Channel and L1-Norm
IEEE Access, 2021 To improve the image quality of the deblurring results restored by existing blind deblurring method, an effective image blind deblurring method based on a single channel and L1-norm is proposed for the blurry images.
Luoyu Zhou, Zhiyang Liu
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Blind Deblurring Based on Sigmoid Function
Sensors, 2021 Blind image deblurring, also known as blind image deconvolution, is a long-standing challenge in the field of image processing and low-level vision. To restore a clear version of a severely degraded image, this paper proposes a blind deblurring algorithm
Shuhan Sun +3 more
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Blind deblurring of natural images [PDF]
2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008 A new method to perform blind image deblurring is proposed. Very few assumptions are made on the blurring filter and on the original image: the blurring filter is assumed to have limited support and the original image is assumed to be a sharp natural image. A new prior is used, which gives higher probability to images with sharp edges.
Mariana S. C. Almeida, Luís B. Almeida
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Infrared Image Deblurring Based on Generative Adversarial Networks
International Journal of Optics, 2021 Blind deblurring of a single infrared image is a challenging computer vision problem. Because the blur is not only caused by the motion of different objects but also by the relative motion and jitter of cameras, there is a change of scene depth.
Yuqing Zhao +4 more
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A Single Image Deblurring Approach Based on a Fractional Order Dark Channel Prior
International Journal of Applied Mathematics and Computer Science, 2022 The dark channel prior has been successfully applied to solve the blind deblurring problem on different scene images. Since the dark channel of the blurry-noise image is similar to that of the corresponding clear image, the sparsity of the dark channel ...
Yu Xiaoyuan, Xie Wei, Yu Jinwei
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