Results 51 to 60 of about 158,938 (168)
, 2010 A denoising technique based on noise invalidation is proposed. The adaptive approach derives a noise signature from the noise order statistics and utilizes the signature to denoise the data. The novelty of this approach is in presenting a general-purpose
Beheshti, Soosan +3 more
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Sparse Representing Denoising of Hyperspectral Data for Water Color Remote Sensing
Applied Sciences, 2022 Hyperspectral data are important for water color remote sensing. The inevitable noise will devalue its application. In this study, we developed a 1-D denoising method for water hyperspectral data, based on sparse representing.
Yulong Guo +7 more
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Boosting of Image Denoising Algorithms
, 2015 In this paper we propose a generic recursive algorithm for improving image denoising methods. Given the initial denoised image, we suggest repeating the following "SOS" procedure: (i) (S)trengthen the signal by adding the previous denoised image to the ...
Elad, Michael, Romano, Yaniv
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From denoising diffusions to denoising Markov models
Journal of the Royal Statistical Society Series B: Statistical MethodologyAbstract Denoising diffusions are state-of-the-art generative models exhibiting remarkable empirical performance. They work by diffusing the data distribution into a Gaussian distribution and then learning to reverse this noising process to obtain synthetic datapoints.
Joe Benton +4 more
openaire +3 more sources
No-reference Image Denoising Quality Assessment [PDF]
, 2018 A wide variety of image denoising methods are available now. However, the performance of a denoising algorithm often depends on individual input noisy images as well as its parameter setting.
Lu, Si
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3D Point Cloud Denoising via Deep Neural Network based Local Surface Estimation
, 2019 We present a neural-network-based architecture for 3D point cloud denoising called neural projection denoising (NPD). In our previous work, we proposed a two-stage denoising algorithm, which first estimates reference planes and follows by projecting ...
Chen, Siheng +2 more
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Overview of Research on Digital Image Denoising Methods
SensorsDuring image collection, images are often polluted by noise because of imaging conditions and equipment limitations. Images are also disturbed by external noise during compression and transmission, which adversely affects consequent processing, like ...
Jing Mao +3 more
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Edge-aware image denoising algorithm
Journal of Algorithms & Computational Technology, 2018 The key of image denoising algorithms is to preserve the details of the original image while denoising the noise in the image. The existing algorithms use the external information to better preserve the details of the image, but the use of external ...
Xiangning Zhang, Yan Yang, Lening Lin
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, 2017 We propose a novel denoising framework for task functional Magnetic Resonance Imaging (tfMRI) data to delineate the high-resolution spatial pattern of the brain functional connectivity via dictionary learning and sparse coding (DLSC). In order to address
AM Wink +13 more
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Reproducibility of graph measures at the subject level using resting‐state fMRI
Brain and Behavior, 2020 Introduction Graph metrics have been proposed as potential biomarkers for diagnosis in clinical work. However, before it can be applied in a clinical setting, their reproducibility should be evaluated.
Qian Ran +5 more
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