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Noise-Adaptive Non-Blind Image Deblurring [PDF]
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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Blind Image Deblurring via Reweighted Graph Total Variation [PDF]
2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017 Blind image deblurring, i.e., deblurring without knowledge of the blur kernel, is a highly ill-posed problem. The problem can be solved in two parts: i) estimate a blur kernel from the blurry image, and ii) given estimated blur kernel, de-convolve blurry
Bai, Yuanchao +3 more
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Effective Alternating Direction Optimization Methods for Sparsity-Constrained Blind Image Deblurring [PDF]
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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Blind image deblurring using class-adapted image priors [PDF]
2017 IEEE International Conference on Image Processing (ICIP), 2017 Blind image deblurring (BID) is an ill-posed inverse problem, usually addressed by imposing prior knowledge on the (unknown) image and on the blurring filter.
Figueiredo, Mário A. T. +1 more
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Blind UAV Images Deblurring Based on Discriminative Networks [PDF]
Sensors, 2018 Unmanned aerial vehicles (UAVs) have become an important technology for acquiring high-resolution remote sensing images. Because most space optical imaging systems of UAVs work in environments affected by vibrations, the optical axis motion and image ...
Ruihua Wang +4 more
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A Fast Nonlinear Sparse Model for Blind Image Deblurring [PDF]
Journal of ImagingBlind image deblurring, which requires simultaneous estimation of the latent image and blur kernel, constitutes a classic ill-posed problem. To address this, priors based on L2, L1, and Lp regularizations have been widely adopted.
Zirui Zhang +8 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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