Results 31 to 40 of about 3,387 (229)
Patch-Based Nonlocal Adaptive Gradient Regularization for Image Restoration in Sensor Networks
IEEE Access, 2019 In this paper, we propose a novel patch-based adaptive nonlocal gradient regularization method for image restoration in sensor networks. It formulates the hyper-Laplacian distribution to regularize the global gradient distribution.
Mingzhu Shi
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Weighted Schatten p-Norm Low Rank Error Constraint for Image Denoising
Entropy, 2021 Traditional image denoising algorithms obtain prior information from noisy images that are directly based on low rank matrix restoration, which pays little attention to the nonlocal self-similarity errors between clear images and noisy images. This paper
Jiucheng Xu, Yihao Cheng, Yuanyuan Ma
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Nonlocal similarity image filtering [PDF]
, 2009 We exploit the recurrence of structures at different locations, orientations and scales in an image to perform denoising. While previous methods based on "nonlocal filtering" identify corresponding patches only up to translations, we consider more ...
Lou, Yifei +7 more
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Weather Radar Image Superresolution Using a Nonlocal Residual Network
Journal of Mathematics, 2021 Accurate and high-resolution weather radar images reflecting detailed structure information of radar echo are vital for analysis and forecast of extreme weather.
Haoxuan Yuan, Qiangyu Zeng, Jianxin He
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Image Denoising Using Nonlocal Means with Shape-Adaptive Patches and New Weights
Shock and Vibration, 2021 Digital images captured from CMOS/CCD image sensors are prone to noise due to inherent electronic fluctuations and low photon count. To efficiently reduce the noise in the image, a novel image denoising strategy is proposed, which exploits both nonlocal ...
Chenglin Zuo, Jun Ma, Hao Xiong, Lin Ran
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An improved nonlocal sparse regularization-based image deblurring via novel similarity criteria
International Journal of Advanced Robotic Systems, 2018 Image deblurring is a challenging problem in image processing, which aims to reconstruct an original high-quality image from its blurred measurement caused by various factors, for example, imperfect focusing caused by the imaging system or different ...
Nannan Wang +3 more
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Superpixel Guide for Transformer Low-Light Image Denoising Method [PDF]
Jisuanji gongchengExisting low-light image denoising methods mainly use the feature extraction and denoising mechanisms of Transformer and Convolutional Neural Networks (CNN).
SONG Quanzhen, CHEN Zuojun, QIN Pinle, ZENG Jianchao
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IET Intelligent Transport Systems, 2023 Spatiotemporal traffic data usually suffers from missing entries in the data acquisition and transmission process. Existing imputation methods only consider the global/local structure of spatiotemporal traffic data, resulting in insufficient estimation ...
Peng‐Ling Wu +2 more
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IEEE Access, 2019 Image deblurring is a classical inverse problem in image processing and computer vision. The vital task is to construct the proper image prior model to obtain the high-quality restored image with salient edges and rich details.
Qiaohong Liu +4 more
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Learning Curvelet-based Directional Dictionaries for Single Image Super Resolution [PDF]
AUT Journal of Electrical Engineering, 2021 Learning and reconstruction-based methods are the two main approaches to the solve single image super resolution (SISR) problem. In this paper, to exploit the advantages of both learning based and reconstruction based approaches, we propose a new SISR ...
Elhameh Mikaeli +2 more
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