Results 11 to 20 of about 539 (168)

Noise Removal Based on Tensor Modelling for Hyperspectral Image Classification

Remote Sensing, 2018
With the current state-of-the-art computer aided manufacturing tools, the spatial resolution of hyperspectral sensors is becoming increasingly higher thus making it easy to obtain much more detailed information of the scene captured.
Salah Bourennane, Caroline Fossati, Tao Lin   +2 more
doaj   +2 more sources

Hyperspectral Image Denoising Based on Deep and Total Variation Priors

Remote Sensing
To address the problems of noise interference and image blurring in hyperspectral imaging (HSI), this paper proposes a denoising method for HSI based on deep learning and a total variation (TV) prior.
Peng Wang, Tianman Sun, Yiming Chen, Lihua Ge, Xiaoyi Wang, Liguo Wang   +5 more
doaj   +2 more sources

Hyperspectral Image Denoising by Pixel-Wise Noise Modeling and TV-Oriented Deep Image Prior

Remote Sensing
Model-based hyperspectral image (HSI) denoising methods have attracted continuous attention in the past decades, due to their effectiveness and interpretability.
Lixuan Yi, Qian Zhao, Zongben Xu
doaj   +2 more sources

Nonlocal Low-Rank Regularized Tensor Decomposition for Hyperspectral Image Denoising

IEEE Transactions on Geoscience and Remote Sensing, 2019
Hyperspectral image (HSI) enjoys great advantages over more traditional image types for various applications due to the extra knowledge available.
Jize Xue, Yongqiang Zhao, Wenzhi Liao
exaly   +2 more sources

Hyperspectral Image Denoising Based on Nonlocal Low-Rank and TV Regularization

Remote Sensing, 2020
Hyperspectral image (HSI) acquisitions are degraded by various noises, among which additive Gaussian noise may be the worst-case, as suggested by information theory.
Xiangyang Kong, Yongqiang Zhao, Jize Xue, Jonathan Cheung-Wai Chan, Zhigang Ren, HaiXia Huang, Jiyuan Zang   +6 more
doaj   +2 more sources

Hybrid-Domain Synergistic Transformer for Hyperspectral Image Denoising

Applied Sciences
Hyperspectral image (HSI) denoising is challenged by complex spatial-spectral noise coupling. Existing deep learning methods, primarily designed for RGB images, fail to address HSI-specific noise distributions and spectral correlations.
Haoyue Li, Di Wu
doaj   +2 more sources

Hyperspectral Image Denoising and Compression Using Optimized Bidirectional Gated Recurrent Unit

Remote Sensing
The availability of a higher resolution fine spectral bandwidth in hyperspectral images (HSI) makes it easier to identify objects of interest in them.
Divya Mohan, Aravinth J, Sankaran Rajendran   +2 more
doaj   +2 more sources

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, Liyuan Li, Xiaoyan Li, Jingwen Zhang, Lixing Zhao, Xiaofeng Su, Fansheng Chen   +6 more
doaj   +1 more source

A new HSI denoising method via interpolated block matching 3D and guided filter [PDF]

PeerJ, 2021
A new hyperspectral images (HSIs) denoising method via Interpolated Block-Matching and 3D filtering and Guided Filtering (IBM3DGF) denoising method is proposed.
Ping Xu, Bingqiang Chen, Jingcheng Zhang, Lingyun Xue, Lei Zhu   +4 more
doaj   +2 more sources

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
core   +1 more source