Image Deblurring Based on Convex Non-Convex Sparse Regularization and Plug-and-Play Algorithm
Algorithms, 2023 Image deblurring based on sparse regularization has garnered significant attention, but there are still certain limitations that need to be addressed.
Yi Wang +4 more
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A domain translation network with contrastive constraint for unpaired motion image deblurring
IET Image Processing, 2023 Most motion deblurring methods require a large amount of paired training data, which is nearly unreachable in practice. To overcome the limitation, a domain translation network with contrastive constraint for unpaired motion image deblurring is proposed.
Bingxin Zhao, Weihong Li
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IEEE Access, 2020 We propose an $L_{p}$ -norm-based sparse regularization model for license plate deblurring, which is motivated by distinctive properties of license plate images. For the blurred images, general deblurring methods may restore a good overall visual effect.
Chenping Zhao +4 more
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Blur2Sharp: A GAN-Based Model for Document Image Deblurring
International Journal of Computational Intelligence Systems, 2021 The advances in mobile technology and portable cameras have facilitated enormously the acquisition of text images. However, the blur caused by camera shake or out-of-focus problems may affect the quality of acquired images and their use as input for ...
Hala Neji +4 more
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Exact, time-dependent analytical equations for spiral trajectories and matching gradient and density-correction waveforms. [PDF]
Magn Reson MedAbstract Purpose To analytically define a spiral waveform and trajectory that match the constraints of gradient frequency, slew rate, and amplitude. Theory and Methods Piecewise analytical solutions for gradient waveforms under the desired constraints are derived using the circle of an involute rather than an Archimedean spiral.
Krishnamoorthy G, Pipe JG.
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Dataset and Network Structure: Towards Frames Selection for Fast Video Deblurring
IEEE Access, 2021 Beyond the underlaying unrealistic presumptions in the existing video deblurring datasets and algorithms which presume that a naturally blurred video is fully blurred. In this work, we define a more realistic video frames averaging-based data degradation
Abdelwahed Nahli +4 more
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A multi-task approach to face deblurring
EURASIP Journal on Wireless Communications and Networking, 2019 Image deblurring is a foundational problem with numerous application, and the face deblurring subject is one of the most interesting branches. We propose a convolutional neural network (CNN)-based architecture that embraces multi-scale deep features.
Ziyi Shen +4 more
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Wasserstein Generative Adversarial Network Based De-Blurring Using Perceptual Similarity
Applied Sciences, 2019 The de-blurring of blurred images is one of the most important image processing methods and it can be used for the preprocessing step in many multimedia and computer vision applications. Recently, de-blurring methods have been performed by neural network
Minsoo Hong, Yoonsik Choe
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Iterative Blind Deconvolution Algorithm for Deblurring a Single PSP/TSP Image of Rotating Surfaces
Sensors, 2018 Imaging of pressure-sensitive paint (PSP) for pressure measurement on moving surfaces is problematic due to the movement of the object within the finite exposure time of the imager, resulting in the blurring of the blade edges.
Anshuman Pandey, James W. Gregory
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Nonlinear Deblurring for Low-Light Saturated Image
Sensors, 2023 Single image deblurring has achieved significant progress for natural daytime images. Saturation is a common phenomenon in blurry images, due to the low light conditions and long exposure times.
Shuning Cao +4 more
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