Results 91 to 100 of about 18,244,520 (347)
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
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 +6 more
wiley +1 more source
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
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 +5 more
wiley +1 more source
Porous Media Characterization by Micro-Tomographic Image Processing [PDF]
, 2011 In this thesis, we have focused our attention on the characterization of porous media through micro-tomographic image processing. A porous medium can be simply seen as a solid material with "holes" in it, which, connected or isolated, may or may not ...
Matrecano, Marcella
core +1 more source
Real Image Denoising With Feature Attention [PDF]
IEEE International Conference on Computer Vision, 2019 Deep convolutional neural networks perform better on images containing spatially invariant noise (synthetic noise); however, its performance is limited on real-noisy photographs and requires multiple stage network modeling.
Saeed Anwar, Nick Barnes
semanticscholar +1 more source
Quantum Boolean image denoising [PDF]
Quantum Information Processing, 2014 A quantum Boolean image processing methodology is presented in this work, with special emphasis in image denoising. A new approach for internal image representation is outlined together with two new interfaces: classical-to-quantum and quantum-to-classical.
openaire +2 more sources
Advanced Functional Materials, EarlyView.Aberrant glycosylation in the glioblastoma tumor microenvironment drives therapeutic resistance. Here, a 3D bioprinted model was engineered by incorporating α‐NeuNAc‐(2→3)‐β‐D‐Gal‐ and chondroitin sulfate. Combined multiplex immunofluorescence and synchrotron‐based nanoCT analysis revealed that glycan‐matrix interactions dictate specific drug‐escape ...
Francesca Cadamuro +25 more
wiley +1 more source
Efficient reconfigurable architectures for 3D medical image compression [PDF]
, 2010 This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Recently, the more widespread use of three-dimensional (3-D) imaging modalities, such as magnetic resonance imaging (MRI), computed tomography (CT ...
Afandi, Ahmad
core +6 more sources
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
core +1 more source