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Blind Deblurring for Saturated Images
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021Blind deblurring has received considerable attention in recent years. However, state-of-the-art methods often fail to process saturated blurry images. The main reason is that pixels around saturated regions are not conforming to the commonly used linear blur model.
Liang Chen 0026 +4 more
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Blind and Semi-Blind Deblurring of Natural Images
IEEE Transactions on Image Processing, 2010A method for blind image deblurring is presented. The method only makes weak assumptions about the blurring filter and is able to undo a wide variety of blurring degradations. To overcome the ill-posedness of the blind image deblurring problem, the method includes a learning technique which initially focuses on the main edges of the image and gradually
Mariana S. C. Almeida, Luís B. Almeida
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Smoothing Priors for Blind Image Deblurring
SIAM Journal on Imaging ScienceszbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fang Li
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2021 6th International Conference for Convergence in Technology (I2CT), 2021
With the growth of technology and digital media, images have started playing a critical role not only in our day-to-day lives but also in fields like Biology and Astronomy to name a few. However, images prove to be useful only when they can successfully convey information to a viewer.
Vahida Attar +3 more
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With the growth of technology and digital media, images have started playing a critical role not only in our day-to-day lives but also in fields like Biology and Astronomy to name a few. However, images prove to be useful only when they can successfully convey information to a viewer.
Vahida Attar +3 more
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Blind face images deblurring with enhancement
Multimedia Tools and Applications, 2020Face images deblurring has achieved advanced development; however, existing methods involve high computational cost problems. Furthermore, the recovered face images by current methods have the problems of over-smooth textures, ringing artifacts, and poor details. We consider the problem of face images deblurring as a semantic generation task.
Qing Qi +3 more
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Enhanced Sparse Model for Blind Deblurring
2020Existing arts have shown promising efforts to deal with the blind deblurring task. However, most of the recent works assume the additive noise involved in the blurring process to be simple-distributed (i.e. Gaussian or Laplacian), while the real-world case is proved to be much more complicated.
Liang Chen +4 more
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Blind Image Deblurring with Outlier Handling
2017 IEEE International Conference on Computer Vision (ICCV), 2017Deblurring images with outliers has attracted considerable attention recently. However, existing algorithms usually involve complex operations which increase the difficulty of blur kernel estimation. In this paper, we propose a simple yet effective blind image deblurring algorithm to handle blurred images with outliers. The proposed method is motivated
Jiangxin Dong +3 more
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Blind image deblurring by game theory
Proceedings of the 2nd International Conference on Networking, Information Systems & Security, 2019In this paper, we present a novel blind deconvolution technique for the restoration of linearly degraded images without explicit knowledge of either the original image or the point spread function (PSF). We propose to determine the optimal image deblurring as a Nash equilibrium, we use two criteria associated with two players.
Driss Meskine +2 more
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Non-uniform Blind Deblurring by Reblurring
2017 IEEE International Conference on Computer Vision (ICCV), 2017We present an approach for blind image deblurring, which handles non-uniform blurs. Our algorithm has two main components: (i) A new method for recovering the unknown blur-field directly from the blurry image, and (ii) A method for deblurring the image given the recovered non-uniform blur-field.
Yuval Bahat, Netalee Efrat, Michal Irani
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An Energy-Scalable Accelerator for Blind Image Deblurring
IEEE Journal of Solid-State Circuits, 2016Camera shake is the leading cause of blur in cell-phone camera images. Removing blur requires deconvolving the blurred image with a kernel which is typically unknown and needs to be estimated from the blurred image. This kernel estimation is computationally intensive and takes several minutes on a CPU which makes it unsuitable for mobile devices.
Priyanka Raina +2 more
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