Results 41 to 50 of about 272,612 (359)
Denoising an Image by Denoising Its Curvature Image [PDF]
SIAM Journal on Imaging Sciences, 2014 The first author acknowledges partial support by European Research Council, Starting Grant ref. 306337, and/nby Spanish grants AACC, ref. TIN2011-15954-E, and Plan Nacional, ref. TIN2012-38112. The second author was supported in part by NSF-DMS #0915219.
Marcelo Bertalmío, Stacey Levine
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Sensors, 2019 In this paper, a novel hybrid method combining adaptive chirp mode pursuit (ACMP) with an adaptive multiscale Savitzky−Golay filter (AMSGF) based on adaptive moving average (AMA) is proposed for offline denoising micro-electromechanical system ...
Jingjing He, Changku Sun, Peng Wang
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MP-PCA denoising for diffusion MRS data: promises and pitfalls
NeuroImage, 2022 Diffusion-weighted (DW) magnetic resonance spectroscopy (MRS) suffers from a lower signal to noise ratio (SNR) compared to conventional MRS owing to the addition of diffusion attenuation. This technique can therefore strongly benefit from noise reduction
Jessie Mosso +5 more
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Universal Framework for Joint Image Restoration and 3D Body Reconstruction
IEEE Access, 2021 Recent works have demonstrated excellent state-of-the-art achievements in image restoration and 3D body reconstruction from an input image. The 3D body reconstruction task, however, relies heavily on the input image’s quality.
Jonathan Samuel Lumentut +5 more
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Adaptive Image Denoising by Targeted Databases [PDF]
, 2014 We propose a data-dependent denoising procedure to restore noisy images. Different from existing denoising algorithms which search for patches from either the noisy image or a generic database, the new algorithm finds patches from a database that ...
Enming Luo +3 more
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Cross-Scale KNN Image Transformer for Image Restoration
IEEE Access, 2023 Numerous image restoration approaches have been proposed based on attention mechanism, achieving superior performance to convolutional neural networks (CNNs) based counterparts.
Hunsang Lee +3 more
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Noise2Void - Learning Denoising From Single Noisy Images [PDF]
Computer Vision and Pattern Recognition, 2018 The field of image denoising is currently dominated by discriminative deep learning methods that are trained on pairs of noisy input and clean target images. Recently it has been shown that such methods can also be trained without clean targets. Instead,
Alexander Krull +2 more
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A denoising stacked autoencoders for transient electromagnetic signal denoising [PDF]
Nonlinear Processes in Geophysics, 2018 Abstract. Transient electromagnetic method (TEM) is extremely important in geophysics. However, the secondary field signal(SFS) in TEM received by coil is easily disturbed by random noise, sensor noise and man-made noise, which results in the difficulty in detecting deep geological information.
F. Lin +9 more
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GCN-Denoiser: Mesh Denoising with Graph Convolutional Networks [PDF]
ACM Transactions on Graphics, 2022 In this article, we present GCN-Denoiser, a novel feature-preserving mesh denoising method based on graph convolutional networks ( GCNs ). Unlike previous learning-based mesh denoising methods that exploit handcrafted or voxel-based representations for feature learning, our method explores ...
Shen, Yuefan +7 more
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Dilated Deep Residual Network for Image Denoising [PDF]
, 2017 Variations of deep neural networks such as convolutional neural network (CNN) have been successfully applied to image denoising. The goal is to automatically learn a mapping from a noisy image to a clean image given training data consisting of pairs of ...
Hu, Kaoning +2 more
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