Results 71 to 80 of about 43,627 (311)

SMDS-Net: Model Guided Spectral-Spatial Network for Hyperspectral Image Denoising [PDF]

, 2022
Deep learning (DL) based hyperspectral images (HSIs) denoising approaches directly learn the nonlinear mapping between noisy and clean HSI pairs. They usually do not consider the physical characteristics of HSIs.
Jiantao Zhou, Jun Zhou, Shuyin Tao, Zhou, Jun, Qian, Yuntao, Yuntao Qian, Xiong, Fengchao, Lu, Jianfeng, Jianfeng Lu, Tao, Shuyin, Zhou, Jiantao, Fengchao Xiong   +11 more
core   +1 more source

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, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Directional edge and texture representations for image processing [PDF]

, 2007
An efficient representation for natural images is of fundamental importance in image processing and analysis. The commonly used separable transforms such as wavelets axe not best suited for images due to their inability to exploit directional ...
Yao, Zhen
core  

Accurate and Fast Image Denoising via Attention Guided Scaling [PDF]

, 2021
Image denoising is a classical topic yet still a challenging problem, especially for reducing noise from the texture information. Feature scaling (e.g., downscale and upscale) is a widely practice in image denoising to enlarge receptive field size and ...
Li, Kai, Zhang, Yulun, Fu, Yun, Li, Kunpeng, Kong, Yu, Sun, Gan   +5 more
core   +1 more source

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

Advanced Engineering Materials, EarlyView.
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle, Cesar Alvarez‐Llamas, Vincent Motto‐Ros, Christophe Dujardin, Jérémie Margueritat, David Rodney   +5 more
wiley   +1 more source

Multi-task learning with self-learning weight for image denoising

Journal of Engineering and Applied Science
Background Image denoising technology removes noise from the corrupted image by utilizing different features between image and noise. Convolutional neural network (CNN)-based algorithms have been the concern of the recent progress on diverse image ...
Qian Xiang, Yong Tang, Xiangyang Zhou
doaj   +1 more source

Multi-View Image Denoising Using Convolutional Neural Network

Sensors, 2019
In this paper, we propose a novel multi-view image denoising algorithm based on convolutional neural network (MVCNN). Multi-view images are arranged into 3D focus image stacks (3DFIS) according to different disparities.
Shiwei Zhou, Yu-Hen Hu, Hongrui Jiang
doaj   +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

Hyperanalytic denoising [PDF]

, 2007
A new threshold rule for the estimation of a deterministic image immersed in noise is proposed. The full estimation procedure is based on a separable wavelet decomposition of the observed image, and the estimation is improved by introducing the new ...
Olhede, SC
core