Results 61 to 70 of about 3,939 (225)

Fast Unmixing of Noisy Hyperspectral Images Based on Vertex Component Analysis and Singular Spectrum Analysis Algorithms

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, Ning Sun, Mingming Xu, Bin Wang, Ling Zhang   +4 more
doaj   +1 more source

Satellite Remote Sensing of Alpine Vegetation Dynamics: Challenges and Perspectives

Global Change Biology, Volume 32, Issue 6, June 2026.
Satellite greening has become a key tool for monitoring alpine vegetation change, but a positive vegetation‐index trend is not an ecological observation in itself. This perspective shows that interpreting alpine greening requires addressing two sequential challenges: methodological complexity, which can bias trends during image processing, and ...
Arthur Bayle
wiley   +1 more source

DISTRIBUTED UNMIXING OF HYPERSPECTRAL DATAWITH SPARSITY CONSTRAINT [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017
Spectral unmixing (SU) is a data processing problem in hyperspectral remote sensing. The significant challenge in the SU problem is how to identify endmembers and their weights, accurately. For estimation of signature and fractional abundance matrices in
S. Khoshsokhan, R. Rajabi, H. Zayyani
doaj   +1 more source

Two‐Dimensional Reconfigurable Photodiode for In‐Sensor Color Filtering and Spectral Logic

Advanced Materials, Volume 38, Issue 26, 8 May 2026.
By harnessing the photodoping of different aggregates, the device exhibits wavelength‐dependent volatile‐to‐nonvolatile photoresponses that can be reconfigured via bias modulation. This enables in‐sensor color filtering and spectral‐encrypted information processing, eliminating reliance on external optical filters or post‐processing algorithms ...
Xiaokun Guo, Yaoqiang Zhou, Yufeng Zhang, Xinyi Zhao, Yue Pang, Lei Tong, Zhipei Sun, Jianbin Xu   +7 more
wiley   +1 more source

A Comprehensive Review of Traditional and Machine Learning‐Assisted Diffuse Optical Spectroscopy and Imaging Techniques for Dermatological Applications

Advanced Photonics Research, Volume 7, Issue 5, May 2026.
This review critically examines clinical studies on both conventional and machine learning (ML)‐integrated diffuse optical spectroscopy and imaging methods for dermatological applications, with a primary focus on the past decade and inclusion of earlier foundational work where appropriate.
Iftak Hussain, Li Xiuting, Randall Ang Jie, Keertana Vinod Ram, Mark Teo Ju Teng, Valerie Xinhui Teo, Malini Olivo, U. S. Dinish   +7 more
wiley   +1 more source

Spatial Structural Priors for Sparse Unmixing of Remotely Sensed Hyperspectral Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
As spectral libraries continue to expand, sparse unmixing has become essential for effectively interpreting mixed pixels in remotely sensed hyperspectral data.
Shaoquan Zhang, Jiajun Zheng, Yuyang Liu, Fan Li, Chengzhi Deng, Antonio Plaza, Lianhui Liang, Zhi He, Shengqian Wang   +8 more
doaj   +1 more source

Deep Learning Integration in Optical Microscopy: Advancements and Applications

Microscopy Research and Technique, Volume 89, Issue 5, Page 791-814, May 2026.
It explores the integration of DL into optical microscopy, focusing on key applications including image classification, segmentation, and computational reconstruction. ABSTRACT Optical microscopy is a cornerstone imaging technique in biomedical research, enabling visualization of subcellular structures beyond the resolution limit of the human eye ...
Pottumarthy Venkata Lahari, Sagnika Dutta, H. Deeksha, Samreen A. Patel, Budheswar Dehury, Nirmal Mazumder   +5 more
wiley   +1 more source

Deep multimodal unmixing of hyperspectral images using Convolutional Block Attention Module (CBAM) and LiDAR features

Egyptian Journal of Remote Sensing and Space Sciences
Hyperspectral image unmixing has garnered considerable attention across various application domains, particularly remote sensing applications. However, relying solely on one modality to distinguish objects with similar spectral information presents ...
M Sreejam, L Agilandeeswari
doaj   +1 more source

Skin Tone in Hyperspectral Imaging and Its Implications for Fairness in AI

Journal of Biophotonics, Volume 19, Issue 4, April 2026.
This study investigates whether skin tone is systematically encoded in hyperspectral imaging (HSI) data and how this influences AI‐based classification. The results show differences in classification performance across skin tones when using both unsupervised and supervised learning methods, indicating the presence of potential bias. ABSTRACT Artificial
Laurie S. van de Weerd, Nick J. van de Berg, L. Lucia Rijstenberg, Ralf L. O. van de Laar, Helena C. van Doorn, Heleen J. van Beekhuizen   +5 more
wiley   +1 more source

TCCU-Net: Transformer and CNN Collaborative Unmixing Network for Hyperspectral Image

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
In recent years, deep-learning-based hyperspectral unmixing techniques have garnered increasing attention and made significant advancements. However, relying solely on the use of convolutional neural network (CNN) or transformer approaches is ...
Jianfeng Chen, Chen Yang, Lan Zhang, Linzi Yang, Lifeng Bian, Zijiang Luo, Jihong Wang   +6 more
doaj   +1 more source