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EdgeGeoDiff: A Novel Two-Stage Diffusion Approach for Precipitation Downscaling with Edge Details and Geographical Priors. [PDF]
Sensors (Basel)Zhang S, Zhang C, Wu T, Zou T, Dong Y.
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Single image super resolution with high resolution dictionary
2011 18th IEEE International Conference on Image Processing, 2011Image super resolution (SR) is a technique to estimate or synthesize a high resolution (HR) image from one or several low resolution (LR) images. This paper proposes a novel framework for single image super resolution based on sparse representation with high resolution dictionary. Unlike the previous methods, the training set is constructed from the HR
Guangwu Mu +4 more
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Single image super-resolution in frequency domain
2012 IEEE Southwest Symposium on Image Analysis and Interpretation, 2012This paper presents a neighborhood dependent components based feature learning (NDCFL) for regression analysis in single image super-resolution. Given a low resolution input, the method uses directional Fourier phase feature components to adaptively learn the regression kernel based on local covariance to estimate the high resolution image.
Mohammad Moinul Islam +3 more
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Single-Image Super-Resolution: A Survey
2019Single-image super-resolution has been broadly applied in many fields such as military term, medical imaging, etc. In this paper, we mainly focus on the researches of recent years and classify them into non-deep learning SR algorithms and deep learning SR algorithms.
Tingting Yao +4 more
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Structure preserving single image super-resolution
2016 IEEE International Conference on Image Processing (ICIP), 2016In this paper, we present a novel structure preserving method for single image super-resolution to well construct edge structures and small detail structures. In our approach, the sharp edges are recovered via a novel edge preserving interpolation technique based on a well estimated gradient field and the edge preserving method, which incorporate the ...
Fan Yang 0053 +5 more
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Single Image Super-Resolution for Medical Image Applications
2020In medical imaging, high-resolution images are expected to have the ability to deliver a more precise diagnosis with the practical application of high-resolution displays. This research proposes a deep learning method for single image super-resolution that learns an end-to-end mapping between the low and high-resolution images.
Tamarafinide V. Dittimi, Ching Y. Suen
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Single Image Super-resolution with Self-similarity
2019 IEEE International Conference on Consumer Electronics (ICCE), 2019Degraded low-resolution (LR) images are often obtained from cameras. Resolution enhancement and image restoration are very practical in many fields such as medical imaging, surveillance system and remote sensing. Single image super-resolution is a technique which reconstruct a restored high-resolution (HR) image from a degraded LR image. In this paper,
Yoojun Nam +3 more
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Subspace Constraint for Single Image Super-Resolution
2021Recently, single image super-resolution (SISR) algorithms based on convolutional neural networks (CNN) have proliferated and achieved significant success. However, most of them use the same constraint to both low-frequency and high-frequency features in the loss function.
Yanlin Zhang, Ding Qin, Xiaodong Gu 0001
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Colorization for Single Image Super Resolution
2010This paper introduces a new procedure to handle color in single image super resolution (SR). Most existing SR techniques focus primarily on enforcing image priors or synthesizing image details; less attention is paid to the final color assignment. As a result, many existing SR techniques exhibit some form of color aberration in the final upsampled ...
Shuaicheng Liu +3 more
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