Results 1 to 10 of about 835 (219)

An Attention-Based 3D Convolutional Autoencoder for Few-Shot Hyperspectral Unmixing and Classification

Remote Sensing, 2023
Few-shot hyperspectral classification is a challenging problem that involves obtaining effective spatial–spectral features in an unsupervised or semi-supervised manner.
Chunyu Li, Rong Cai, Junchuan Yu
doaj   +1 more source

An Elliptic Kernel Unsupervised Autoencoder—Graph Convolutional Network Ensemble Model for Hyperspectral Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Spectral unmixing is an important technique in remote sensing for analyzing hyperspectral images to identify endmembers and estimate fractional abundance maps.
Estefania Alfaro-Mejia, Carlos J. Delgado, Vidya Manian   +2 more
doaj   +1 more source

A blind convolutional deep autoencoder for spectral unmixing of hyperspectral images over waterbodies

Frontiers in Earth Science, 2023
Harmful algal blooms have dangerous repercussions for biodiversity, the ecosystem, and public health. Automatic identification based on remote sensing hyperspectral image analysis provides a valuable mechanism for extracting the spectral signatures of ...
Estefanía Alfaro-Mejía, Vidya Manian, Joseph D. Ortiz, Roger P. Tokars   +3 more
doaj   +1 more source

An Automatic Sparse Pruning Endmember Extraction Algorithm with a Combined Minimum Volume and Deviation Constraint

Remote Sensing, 2018
In this paper, an automatic sparse pruning endmember extraction algorithm with a combined minimum volume and deviation constraint (SPEEVD) is proposed.
Huali Li, Jun Liu, Haicong Yu
doaj   +1 more source

Adaptive Background Endmember Extraction for Hyperspectral Subpixel Object Detection

Remote Sensing
Subpixel object detection presents a significant challenge within the domain of hyperspectral image (HSI) processing, primarily due to the inherently limited spatial resolution of imaging spectrometers.
Lifeng Yang, Xiaorui Song, Bin Bai, Zhuo Chen   +3 more
doaj   +1 more source

Incorporating band selection in the spatial selection of spectral endmembers

International Journal of Applied Earth Observations and Geoinformation, 2020
The impact of band selection on endmember selection is seldom explored in the analysis of hyperspectral imagery. This study incorporates the N-dimensional Spectral Solid Angle (NSSA) band selection tool into the Spectral-Spatial Endmember Extraction ...
Yaqian Long, Benoit Rivard, Derek Rogge
doaj   +1 more source

Hyperspectral Unmixing Using Frequency-Adaptive Convolutional-Mamba Network

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
In recent years, deep learning (DL) has achieved remarkable progress in hyperspectral unmixing (HU) owing to its powerful feature extraction and modeling capabilities.
Zhuoyi Zhao, Xiang Xu, Chuiyi Deng, Yanyin Guo, Junwei Li, Antonio Plaza   +5 more
doaj   +1 more source

Unsupervised Hyperspectral Unmixing Based on Multi-Faceted Graph Representation and Curriculum Learning

Remote Sensing
Hyperspectral unmixing aims to estimate endmember spectra and their corresponding abundance fractions at the subpixel scale, which is a critical preprocessing step for quantitative analysis of hyperspectral remote sensing imagery.
Ran Liu, Junfeng Pu, Yanru Chen, Yanling Miao, Dawei Liu, Qi Wang   +5 more
doaj   +1 more source

Fractional Impervious Surface Mapping on Multispectral Images With Visible Shadows via a Bundle-Based Sparse Unmixing Model

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Impervious surface abundance (ISA) is an important indicator for monitoring urbanization and environmental disaster management processes. Commonly used spectral unmixing techniques extract ISA in the form of mixed pixels; however, in previous ...
Yanze Liu, Dacheng Li, Wei Xiong, Qijin Han, Lingling Ma   +4 more
doaj   +1 more source

Fast Endmember Extraction for Massive Hyperspectral Sensor Data on GPUs

International Journal of Distributed Sensor Networks, 2013
Hyperspectral imaging sensor becomes increasingly important in multisensor collaborative observation. The spectral mixture problem seriously influences the efficiency of hyperspectral data exploitation, and endmember extraction is one of the key issues ...
Zebin Wu, Shun Ye, Jie Wei, Zhihui Wei, Le Sun, Jianjun Liu   +5 more
doaj   +1 more source