Results 31 to 40 of about 2,688,199 (290)
Unfolding the Alternating Optimization for Blind Super Resolution
CoRR, 2020 Conference on Neural Information Processing Systems (NeurIPS ...
Zhengxiong Luo 0001 +4 more
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Blind Super-Resolution via Projected Gradient Descent
2022 IEEE International Symposium on Information Theory (ISIT), 2022 Blind super-resolution can be cast as low rank matrix recovery problem by exploiting the inherent simplicity of the signal. In this paper, we develop a simple yet efficient nonconvex method for this problem based on the low rank structure of the vectorized Hankel matrix associated with the target matrix.
Sihan Mao, Jinchi Chen
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Kernel-aware Burst Blind Super-Resolution
CoRR, 2021 Burst super-resolution (SR) technique provides a possibility of restoring rich details from low-quality images. However, since real world low-resolution (LR) images in practical applications have multiple complicated and unknown degradations, existing non-blind (e.g., bicubic) designed networks usually suffer severe performance drop in recovering high ...
Wenyi Lian, Shanglian Peng
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Sensors, 2022 To date, the best-performing blind super-resolution (SR) techniques follow one of two paradigms: (A) train standard SR networks on synthetic low-resolution–high-resolution (LR–HR) pairs or (B) predict the degradations of an LR image and then use these to
Matthew Aquilina +5 more
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StarSRGAN: Improving Real-World Blind Super-Resolution
, 2023 This research is funded by Univer sity of Science, VNU-HCM project CNTT 2023-0The aim of blind super-resolution (SR) in computer vision is to improve the resolution of an image without prior knowledge of the degradation process that caused the image to ...
Vo, Khoa D., Bui, Len T.
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Mathematical theory of blind super-resolution: multidimensional cases [PDF]
, 2021 Super-resolution is a fundamental problem in signal processing that concerns with extracting fine-scale data from low-resolution information. In this thesis, we focus on developing atomic norm-based algorithms for blind super-resolution. Due to the extra
Suliman, Mohamed Abdalla Elhag
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Contrastive learning for a single historical painting’s blind super-resolution
Visual Informatics, 2021 Most of the existing blind super-resolution(SR) methods explicitly estimate the kernel in pixel space, which usually has a large deviation and results in poor SR performance.
Hongzhen Shi +4 more
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Kernelized Back-Projection Networks for Blind Super Resolution [PDF]
, 2023 Since non-blind Super Resolution (SR) fails to super-resolve Low-Resolution (LR) images degraded by arbitrary degradations, SR with the degradation model is required.
Maeda, Takahiro +4 more
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Joint Blind Super-Resolution and Shadow Removing
IEICE Transactions on Information and Systems, 2007 Most learning-based super-resolution methods neglect the illumination problem. In this paper we propose a novel method to combine blind single-frame super-resolution and shadow removal into a single operation. Firstly, from the pattern recognition viewpoint, blur identification is considered as a classification problem.
Jianping Qiao, Ju Liu, Yen-Wei Chen
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IET Image Processing, 2021 The current super‐resolution (SR) deep network is mainly applied to the common image and pays little attention to the image with noise. The remote sensing image contains much noise, so that the SR reconstruction effect is not satisfactory.
Xin Yang +3 more
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