Neural blind deconvolution for deblurring and supersampling PSMA PET [PDF]
Objective: To simultaneously deblur and supersample prostate specific membrane antigen (PSMA) positron emission tomography (PET) images using neural blind deconvolution. Approach: Blind deconvolution is a method of estimating the hypothetical "deblurred"
Sample, Caleb +6 more
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Deep learning in motion deblurring: current status, benchmarks and future prospects
Motion deblurring is one of the fundamental problems of computer vision and has received continuous attention. The variability in blur, both within and across images, imposes limitations on non-blind deblurring techniques that rely on estimating the blur
Li, Zhongbo +5 more
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FMD-cGAN: Fast Motion Deblurring using Conditional Generative Adversarial Networks
, 2021 In this paper, we present a Fast Motion Deblurring-Conditional Generative Adversarial Network (FMD-cGAN) that helps in blind motion deblurring of a single image. FMD-cGAN delivers impressive structural similarity and visual appearance after deblurring an
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Image Deblurring in Demanding Conditions
, 2020 Title: Image Deblurring in Demanding Conditions Author: Jan Kotera Department: Institute of Information Theory and Automation, Czech Academy of Sciences Supervisor: Doc. Ing.
Kotera, Jan
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Blind Image Deblurring with FFT-ReLU Sparsity Prior
Blind image deblurring is the process of recovering a sharp image from a blurred one without prior knowledge about the blur kernel. It is a small data problem, since the key challenge lies in estimating the unknown degrees of blur from a single image or ...
Majumder, Prothito Shovon +2 more
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Blind Deblurring Method for CASEarth Multispectral Images Based on Inter-Band Gradient Similarity Prior. [PDF]
Sensors (Basel)Zhu M, Liu J, Wang F.
europepmc +1 more source
Non-Blind Image Deblurring via Shear Total Variation Norm
In this paper, we propose a novel shear gradient operator by combining the shear and gradient operators. The shear gradient operator performs well to capture diverse directional information in the image gradient domain.
Weiyu LI, Qiuli GAO, Tao ZHANG
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MMBM-Driven and IMU-Assisted Adaptive Deblurring for Periodic Rotational-Scanning Panoramic Imaging Systems. [PDF]
Sensors (Basel)Wang Y +5 more
europepmc +1 more source
DWDN: Deep Wiener Deconvolution Network for Non-Blind Image Deblurring [PDF]
We present a simple and effective approach for non-blind image deblurring, combining classical techniques and deep learning. In contrast to existing methods that deblur the image directly in the standard image space, we propose to perform an explicit ...
Roth, Stefan +2 more
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Adaptive super-resolution UAV inspection and image perception strategy planning for distribution networks. [PDF]
Sci RepLiu J, Xu G, Ma Y.
europepmc +1 more source