Results 271 to 280 of about 10,813,722 (307)
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Bayesian Methods for Image Super-Resolution
The Computer Journal, 2008We present a novel method of Bayesian image super-resolution in which marginalization is carried out over latent parameters such as geometric and photometric registration and the image point-spread function. Related Bayesian super-resolution approaches marginalize over the high-resolution image, necessitating the use of an unfavourable image prior ...
Pickup, LC +3 more
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Image and Vision Computing, 2006
Abstract The shortcomings in commonly used kernel-based super-resolution drive the study of improved super-resolution algorithms of higher quality. In the past years a wide range of very different approaches has been taken to improve super-resolution.
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Abstract The shortcomings in commonly used kernel-based super-resolution drive the study of improved super-resolution algorithms of higher quality. In the past years a wide range of very different approaches has been taken to improve super-resolution.
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Deep Learning for Image Super-Resolution: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021Steven Hoi, Zhihao Wang
exaly
Image super-resolution: A comprehensive review, recent trends, challenges and applications
Information Fusion, 2023Vishal Goyal +2 more
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Super-resolution image reconstruction
IEEE Signal Processing Magazine, 2003Moon Gi Kang, Subhasis Chaudhuri
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Real-world single image super-resolution: A brief review
Information Fusion, 2022Honggang Chen, Ce Zhu, Xiaohai He
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Hyperspectral Image Super-Resolution Meets Deep Learning: A Survey and Perspective
IEEE/CAA Journal of Automatica Sinica, 2023Xinya Wang, Jiayi Ma, Yingsong Cheng
exaly
Contour enhanced image super-resolution
Journal of Visual Communication and Image Representation, 2022Linhua Kong +3 more
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