Results 81 to 90 of about 539 (168)

A fully automated, faster noise rejection approach to increasing the analytical capability of chemical imaging for digital histopathology.

PLoS ONE, 2019
Chemical hyperspectral imaging (HSI) data is naturally high dimensional and large. There are thus inherent manual trade-offs in acquisition time, and the quality of data. Minimum Noise Fraction (MNF) developed by Green et al.
Soumyajit Gupta, Shachi Mittal, Andre Kajdacsy-Balla, Rohit Bhargava, Chandrajit Bajaj   +4 more
doaj   +1 more source

Fast Hyperspectral Image Denoising and Inpainting Based on Low-Rank and Sparse Representations

, 2018
This paper introduces two very fast and competitive hyperspectral image (HSI) restoration algorithms: fast hyperspectral denoising (FastHyDe), a denoising algorithm able to cope with Gaussian and Poissonian noise, and fast hyperspectral inpainting ...
Bioucas-Dias, José M., Lina Zhuang, Zhuang, Lina, Jose M. Bioucas-Dias   +3 more
core   +1 more source

An end-to-end framework for joint denoising and classification of hyperspectral images

, 2023
Image denoising and classification are typically conducted separately and sequentially according to their respective objectives. In such a setup, where the two tasks are decoupled, the denoising operation does not optimally serve the classification task ...
Li, Xian, Pizurica, Aleksandra, Gu, Yanfeng, Ding, Mingli   +3 more
core   +1 more source

SSUMamba: Spatial-Spectral Selective State Space Model for Hyperspectral Image Denoising

Denoising is a crucial preprocessing step for hyperspectral images (HSIs) due to noise arising from intraimaging mechanisms and environmental factors. Long-range spatial-spectral correlation modeling is beneficial for HSI denoising but often comes with ...
Fu, G, Xiong, F, Zhou, J, Lu, J
core   +1 more source

Hyperspectral Image Mixed Noise Removal via Double Factor Total Variation Nonlocal Low-Rank Tensor Regularization

Remote Sensing
A hyperspectral image (HSI) is often corrupted by various types of noise during image acquisition, e.g., Gaussian noise, impulse noise, stripes, deadlines, and more. Thus, as a preprocessing step, HSI denoising plays a vital role in many subsequent tasks.
Yongjie Wu, Wei Xu, Liangliang Zheng
doaj   +1 more source

Hyperspectral Image Denoising via Spatial-Spectral Recurrent Transformer

Hyperspectral images (HSIs) often suffer from noise arising from both intra-imaging mechanisms and environmental factors. Leveraging domain knowledge specific to HSIs, such as global spectral correlation (GSC) and non-local spatial self-similarity (NSS),
Zhou, Jun, Qian, Yuntao, Xiong, Fengchao, Lu, Jianfeng, Zhou, Jiantao, Fu, Guanyiman   +5 more
core   +1 more source

Weighted Total Variation for Hyperspectral Image Denoising Based on Hyper-Laplacian Scale Mixture Distribution

Remote Sensing
Conventional total variation (TV) regularization methods based on Laplacian or fixed-scale Hyper-Laplacian priors impose uniform sparsity penalties on gradients.
Xiaoyu Yu, Jianli Zhao, Sheng Fang, Tianheng Zhang, Liang Li, Xinyue Huang   +5 more
doaj   +1 more source

Unsupervised Adaptation Learning for Real Multiplatform Hyperspectral Image Denoising

Real hyperspectral images (HSIs) are ineluctably contaminated by diverse types of noise, which severely limits the image usability. Recently, transfer learning has been introduced in hyperspectral denoising networks to improve model generalizability ...
Heiskanen, Janne, Luo, Zhaozhi, Zhong, Yanfei, Wang, Xinyu, Pellikka, Petri   +4 more
core   +1 more source

Fast Hyperspectral image Denoising based on low rank and sparse representations

, 2016
The very high spectral resolution of Hyperspectral Images (HSIs) enables the identification of materials with subtle differences and the extraction subpixel information.
Bioucas-Dias, Jose M., Lina Zhuang, Zhuang, Lina, Jose M. Bioucas-Dias   +3 more
core   +1 more source

Non-Local Meets Global: An Integrated Paradigm for Hyperspectral Denoising

, 2019
Non-local low-rank tensor approximation has been developed as a state-of-the-art method for hyperspectral image (HSI) denoising. Unfortunately, while their denoising performance benefits little from more spectral bands, the running time of these methods ...
Naoto Yokoya, Yao, Quanming, Yokoya, Naoto, Wei He, Quanming Yao, Chao Li, Li, Chao, He, Wei, Zhao, Qibin, Qibin Zhao   +9 more
core   +1 more source