Results 51 to 60 of about 17,318 (265)
Iterative Refinement Network for Hyperspectral Image Denoising
, 2023 Hyperspectral image (HSI) denoising is an important pre-processing procedure for subsequent tasks. Learning a direct mapping from the observed noisy HSI to its clean counterpart is challenging, especially in the case of very severe noise.
Xiong, F, Zhou, J, Zhao, Z, Qian, Y
core +1 more source
Memory and Resting‐State Connectivity in Acute Transient Global Amnesia: A Case–Control fMRI Study
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background and Objectives Transient global amnesia (TGA) is a striking model of isolated amnesia. While hippocampal lesions are well described, the network‐level mechanisms and the precise neuropsychological profile remain debated. Our objective was thus to characterize functional and neuropsychological correlates of acute TGA and their ...
Elias El Otmani +10 more
wiley +1 more source
Complex Discrete Wavelet Transform-Based Image Denoising [PDF]
Engineering and Technology Journal, 2011 Dual tree complex discrete wavelet transform is implemented for denoising as an important image processing application. Two wavelet trees are used, one generating the real part of the wavelet coefficients tree and the other generating the imaginary part ...
Hadeel N. Abdullah +2 more
doaj +1 more source
Multi-Scale Feature Learning Convolutional Neural Network for Image Denoising
Sensors, 2023 Affected by the hardware conditions and environment of imaging, images generally have serious noise. The presence of noise diminishes the image quality and compromises its effectiveness in real-world applications.
Shuo Zhang +4 more
doaj +1 more source
Image volume denoising using a Fourier-wavelet basis [PDF]
, 2003 A novel approach to the removal of noise from threedimensional image data is described. The image sequence is represented using a non-adaptive wavelet basis, carefully chosen for its ability to compactly represent locally planar surfaces.
Wilson, Roland +3 more
core
Multiresolution analysis using wavelet, ridgelet, and curvelet transforms for medical image segmentation [PDF]
, 2011 Copyright @ 2011 Shadi AlZubi et al. This article has been made available through the Brunel Open Access Publishing Fund.The experimental study presented in this paper is aimed at the development of an automatic image segmentation system for classifying ...
Alzubi, S +5 more
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Advanced Engineering Materials, EarlyView.New features on yttria‐stabilized zirconia after exposure at 1500°C: Newly discovered pyramidal structures on an old material. After exposure at 1550°C on the cross section of YSZ new features, namely pyramidal structures are discovered. These structures grow with time, increase in numbers, appear as singularities, are often arranged in strings, and ...
Doris Sebold +2 more
wiley +1 more source
Deep Parameterized Neural Networks for Hyperspectral Image Denoising
, 2023 Sparse representation (SR)-based hyperspectral image (HSI) denoising methods normally average the local denoising results of multiple overlapped cubes to recover the whole HSI.
Jiantao Zhou +8 more
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Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
Deep Neural Network for Image Super Resolution Driven by Prior Denoising
Nantong Daxue xuebao. Ziran kexue ban, 2021 In order to improve image super resolution, a double layer convolution neural network in image denoising is embedded in image restoration tasks. The image super resolution method driven by prior denoising with deep neural network is proposed.
CHENG Fanqiang;ZHU Yonggui;, ZHU Yonggui
doaj +1 more source