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Stereoscopic video deblurring transformer
Scientific ReportsStereoscopic cameras, such as those in mobile phones and various recent intelligent systems, are becoming increasingly common. Multiple variables can impact the stereo video quality, e.g., blur distortion due to camera/object movement.
Hassan Imani +3 more
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Deblurring gaussian blur [PDF]
Computer Vision, Graphics, and Image Processing, 1986 Summary: Gaussian blur, or convolution against a Gaussian kernel, is a common model for image and signal degradation. In general, the process of reversing Gaussian blur is unstable, and cannot be represented as a convolution filter in the spatial domain.
Hummel, Robert A. +2 more
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CORE-Deblur: Parallel MRI Reconstruction by Deblurring using compressed sensing [PDF]
Magnetic Resonance Imaging, 2020 In this work we introduce a new method that combines Parallel MRI and Compressed Sensing (CS) for accelerated image reconstruction from subsampled k-space data. The method first computes a convolved image, which gives the convolution between a user-defined kernel and the unknown MR image, and then reconstructs the image by CS-based image deblurring, in
Shimron, E., Webb, A.G., Azhari, H.
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Direct Sparse Deblurring [PDF]
Journal of Mathematical Imaging and Vision, 2010 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lou, Yifei +2 more
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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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Symmetrization techniques in image deblurring [PDF]
ETNA - Electronic Transactions on Numerical Analysis, 2023 This paper presents a couple of preconditioning techniques that can be used to enhance the performance of iterative regularization methods applied to image deblurring problems with a variety of point spread functions (PSFs) and boundary conditions. More precisely, we first consider the anti-identity preconditioner, which symmetrizes the coefficient ...
Donatelli M., Ferrari P., Gazzola S.
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Joint Face Super-Resolution and Deblurring Using Generative Adversarial Network
IEEE Access, 2020 Facial image super-resolution (SR) is an important aspect of facial analysis, and it can contribute significantly to tasks such as face alignment, face recognition, and image-based 3D reconstruction. Recent convolutional neural network (CNN) based models
Jung Un Yun, Byungho Jo, In Kyu Park
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Real Image Deblurring Based on Implicit Degradation Representations and Reblur Estimation
Applied Sciences, 2023 Most existing image deblurring methods are based on the estimation of blur kernels and end-to-end learning of the mapping relationship between blurred and sharp images.
Zihe Zhao +4 more
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Graph Laplacian for image deblurring [PDF]
ETNA - Electronic Transactions on Numerical Analysis, 2021 Image deblurring is relevant in many fields of science and engineering. To solve this problem, many different approaches have been proposed and among the various methods, variational ones are extremely popular. These approaches are characterized by substituting the original problem with a minimization one where the functional is composed of two terms ...
Bianchi D. +3 more
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Two-Level Wavelet-Based Convolutional Neural Network for Image Deblurring
IEEE Access, 2021 Image deblurring aims to restore the latent sharp image from the blurred one. In recent years, some learning-based image deblurring methods have achieved significant advances.
Yeyun Wu, Pan Qian, Xiaofeng Zhang
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