Results 91 to 100 of about 539 (168)

UEG Week 2025 Poster Presentations

United European Gastroenterology Journal, Volume 13, Issue S8, Page S803-S1476, October 2025.
wiley   +1 more source

Hyperspectral image denoising via self-modulating convolutional neural networks

Compared to natural images, hyperspectral images (HSIs) consist of a large number of bands, with each band capturing different spectral information from a certain wavelength, even some beyond the visible spectrum.
Erkut Erdem, Orhan Torun, Nevrez Imamoglu, Erdem, Erkut, Torun, Orhan, Seniha Esen Yuksel, Aykut Erdem, Erdem, Aykut, Imamoglu, Nevrez, Yuksel, Seniha Esen   +9 more
core   +1 more source

Iteratively Regularizing Hyperspectral and Multispectral Image Fusion With Framelets

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral (HS) and multispectral (MS) image fusion mainly focuses on transferring spatial details from high spatial resolution (HR) MS images (MSIs) to low spatial resolution (LR) HS images (HSIs).
Xiangfei Shen, Lihui Chen, Haijun Liu, Xichuan Zhou, Wenxing Bao, Ling Tian, Gemine Vivione, Jocelyn Chanussot   +7 more
doaj   +1 more source

Hyperspectral Image Denoising Using Low Pass Sparse Banded Filter Matrix for Improved Sparsity Based Classification

, 2015
The recent advance in sensor technology is a boon for hyperspectral remote sensing. Though Hyperspectral images (HSI) are captured using these advanced sensors, they are highly prone to issues like noise, high dimensionality of data and spectral mixing ...
Aswathy, C., Sowmya, V., Soman, K.P.
core   +1 more source

Generative Artificial Intelligence for Hyperspectral Sensor Data: A Review

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Airborne platforms and satellites provide rich sensor data in the form of hyperspectral images (HSI), which are crucial for numerous vision-related tasks, such as feature extraction, image enhancement, and data synthesis.
Diaa Addeen Abuhani, Imran Zualkernan, Raghad Aldamani, Mohamed Alshafai   +3 more
doaj   +1 more source

Hyperspectral Mixed Denoising via Spectral Difference-Induced Total Variation and Low-Rank Approximation

, 2018
Exploration of multiple priors on observed signals has been demonstrated to be one of the effective ways for recovering underlying signals. In this paper, a new spectral difference-induced total variation and low-rank approximation (termed SDTVLA) method
Zebin Wu, Le Sun, Tianming Zhan, Liang Xiao, Byeungwoo Jeon   +4 more
core   +1 more source

Wavelet-Enhanced Weighted and Dense Cross-Scope Transformer for Hyperspectral Image Super-Resolution

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral image (HSI) super-resolution is crucial to enhance the spatial detail of hyperspectral data and has achieved notable advancements in recent years.
Kaiyu Zhang, Ping Xu, Jiayi Chen, Xiaoli Li   +3 more
doaj   +1 more source

Unmixing diffusion for self-supervised hyperspectral image denoising

Hyperspectral images (HSIs) have extensive applications in various fields such as medicine, agriculture, and industry. Nevertheless, acquiring high signal-to-noise ratio HSI poses a challenge due to narrow-band spectral filtering.
Luong, Hiep, Zeng, Haijin, Chen, Yongyong, Cao, Jiezhang, Zhang, Kai, Philips, Wilfried   +5 more
core   +1 more source

Hyperspectral Image Denoising Based on Spectral Dictionary Learning and Sparse Coding

, 2019
Processing and applications of hyperspectral images (HSI) are limited by the noise component. This paper establishes an HSI denoising algorithm by applying dictionary learning and sparse coding theory, which is extended into the spectral domain.
Lingda Wu, Hongxing Hao, Xiaorui Song, Wanpeng Xu   +3 more
core   +1 more source

Iterative Nonparametric Bayesian CP Decomposition for Hyperspectral Image Denoising

Hyperspectral image (HSI) denoising relies on exploiting the multiway correlations hidden in the clean signals to discriminate between the randomness of measurement noise.
Zhang, Xuesong, Lai, Jinzhi, Liu, Wei, Jiang, Kaiwen   +3 more
core   +1 more source