Results 31 to 40 of about 1,639 (207)
Nonlocal Spatial–Spectral Neural Network for Hyperspectral Image Denoising
, 2022 Hyperspectral image (HSI) denoising is an essential preprocessing step to improve the quality of HSIs. The difficulty of HSI denoising lies in effectively modeling the intrinsic characteristics of HSIs, such as spatial-spectral correlation (SSC), global ...
Zhou, Jun +4 more
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Deep Convolutional Network Aided by Non-Local Method for Hyperspectral Image Denoising
IEEE Access, 2023 This paper introduces a new hyperspectral image denoising method called Non-local Convolutional Neural Network Denoiser (NL-CNND). The technique exploits data in four bands adjacent to the target one as additional information for the restoring process ...
Gabriel A. De Oliveira +3 more
doaj +1 more source
Hyperspectral image unmixing using a multiresolution sticky HDP [PDF]
, 2012 This paper is concerned with joint Bayesian endmember extraction and linear unmixing of hyperspectral images using a spatial prior on the abundance vectors.We propose a generative model for hyperspectral images in which the abundances are sampled from a ...
Hero, Alfred O. +3 more
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Canadian Journal of Remote Sensing, 2020 Efficient denoising is of great significance to unmixing hyperspectral images. In the present study, a fast unmixing method for noisy hyperspectral images based on the combination of vertex component analysis and singular spectrum analysis is proposed ...
Dongmei Song +4 more
doaj +1 more source
Mixed Attention Network for Hyperspectral Image Denoising
CoRR, 2023 Hyperspectral image denoising is unique for the highly similar and correlated spectral information that should be properly considered. However, existing methods show limitations in exploring the spectral correlations across different bands and feature interactions within each band.
Zeqiang Lai, Ying Fu 0001
openaire +2 more sources
SMDS-Net: Model Guided Spectral-Spatial Network for Hyperspectral Image Denoising
, 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 +11 more
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Hyperspectral image denoising with enhanced multivariance product representation [PDF]
, 2022 Hyperspectral images are used in many different fields due to their ability to capture wide areas and rich spectrality. However, applications on hyperspectral image (HSI) are affected or limited by various types of noise.
Ozay, Evrim Korkmaz, Tunga, Burcu
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Noise Reduction in Hyperspectral Imagery: Overview and Application
Remote Sensing, 2018 Hyperspectral remote sensing is based on measuring the scattered and reflected electromagnetic signals from the Earth’s surface emitted by the Sun. The received radiance at the sensor is usually degraded by atmospheric effects and instrumental (sensor ...
Behnood Rasti +4 more
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Sensors, 2015 Processing line-by-line and in real-time can be convenient for some applications of line-scanning hyperspectral imaging technology. Some types of processing, like inverse modeling and spectral analysis, can be sensitive to noise.
Asgeir Bjorgan, Lise Lyngsnes Randeberg
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A Denoising Network Based on Frequency-Spectral- Spatial-Feature for Hyperspectral Image
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 The quality of hyperspectral images seriously impedes subsequent high-level vision tasks such as image segmentation, image encoding, and target detection.
Siqi Wang +6 more
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