Results 41 to 50 of about 6,229 (197)

A New Fast Sparse Unmixing Algorithm Based on Adaptive Spectral Library Pruning and Nesterov Optimization

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
In recent years, hyperspectral sparse unmixing (HSU) has garnered extensive research and attention due to its unique characteristic of not requiring the estimation of endmembers and their number.
Kewen Qu, Fangzhou Luo, Huiyang Wang, Wenxing Bao   +3 more
doaj   +1 more source

Robust Linear Spectral Unmixing Using Anomaly Detection [PDF]

IEEE Transactions on Computational Imaging, 2015
This paper presents a Bayesian algorithm for linear spectral unmixing of hyperspectral images that accounts for anomalies present in the data. The model proposed assumes that the pixel reflectances are linear mixtures of unknown endmembers, corrupted by an additional nonlinear term modelling anomalies and additive Gaussian noise.
Altmann, Yoann, McLaughlin, Steve, Hero, Alfred   +2 more
openaire   +2 more sources

High‐Content SRS Imaging Unveils Altered Cholesterol Metabolism in Ovarian Cancers Under CAR‐T Treatment

Advanced Science, EarlyView.
High‐content Stimulated Raman Scattering (SRS) Imaging reveals that ovarian cancer cells surviving Chimeric Antigen Receptor (CAR) ‐T cell challenge exhibit increased cholesterol esterification. Pharmacological inhibition of this pathway with Avasimibe significantly enhances CAR‐T induced killing of ovarian cancer cells by reducing cancer cell ...
Chinmayee V. Prabhu Dessai, Zhuoying Huang, Haonan Lin, Guangrui Ding, Hongjian He, Menna Siddiqui, Meng Zhang, Wilson Wong, Ji‐Xin Cheng   +8 more
wiley   +1 more source

ASSESSING AND COMPARING THE PERFORMANCE OF ENDMEMBER EXTRACTION METHODS IN MULTIPLE CHANGE DETECTION USING HYPERSPECTRAL DATA [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019
Endmember extraction is a process to identify the hidden pure source signals from the mixture. Endmember finding has become increasingly important in hyperspectral data exploitation because endmembers can be used to specify unknown particular spectral ...
H. Jafarzadeh, M. Hasanlou
doaj   +1 more source

Spectral Unmixing of Hyperspectral Imagery Using Multilayer NMF [PDF]

IEEE Geoscience and Remote Sensing Letters, 2015
5 pages ...
Roozbeh Rajabi, Hassan Ghassemian
openaire   +2 more sources

Real‐Time In Vivo Visualization of Tumor‐Associated Macrophage Reprogramming Using a Nitric Oxide‐Activatable NIR‐II Nanoinducer

Advanced Science, EarlyView.
Reprogramming tumor‐associated macrophages is a promising therapeutic strategy for solid tumors. Here, a nitric oxide (NO)‐activatable NIR‐II fluorescence/photoacoustic nanoinducer (I/E@M2pep) that simultaneously facilitates and visualizes the repolarization of TAMs to an M1‐like phenotype is reported, thereby enhancing anti‐tumor efficacy through M1 ...
Qian Chen, Meng Li, Tuanwei Li, Chen Yang, Xiaohu Yang, Hongchao Yang, Yejun Zhang, Chunyan Li, Qiangbin Wang   +8 more
wiley   +1 more source

Multiband Image Fusion Based on Spectral Unmixing [PDF]

IEEE Transactions on Geoscience and Remote Sensing, 2016
This paper presents a multi-band image fusion algorithm based on unsupervised spectral unmixing for combining a high-spatial low-spectral resolution image and a low-spatial high-spectral resolution image. The widely used linear observation model (with additive Gaussian noise) is combined with the linear spectral mixture model to form the likelihoods of
Wei, Qi, Bioucas-Dias, José M., Dobigeon, Nicolas, Tourneret, Jean-Yves, Chen, Marcus, Godsill, Simon   +5 more
openaire   +4 more sources

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source

Research on the Hyperspectral-based Unmixing Model of Composite Pigments on Mural Surfaces [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Murals constitute an invaluable component of cultural heritage, encapsulating profound artistic and historical significance. Hyperspectral remote sensing, as a non-destructive testing technique, offers an effective means for analysing and identifying ...
Y. Zhang, Y. Zhang, S. Lyu, S. Lyu, M. Hou, M. Hou, J. Guo, J. Yan, J. Yan   +8 more
doaj   +1 more source

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source