Results 31 to 40 of about 91,296 (293)
Nonlinear spectral unmixing of hyperspectral images using Gaussian processes [PDF]
, 2012 This paper presents an unsupervised algorithm for nonlinear unmixing of hyperspectral images. The proposed model assumes that the pixel reflectances result from a nonlinear function of the abundance vectors associated with the pure spectral components ...
Altmann, Yoann +5 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Band redundancy and limitation of labeled samples restrict the development of hyperspectral image classification (HSIC) greatly. To address the earlier issues, the classification models such as subspace-based support vector machines, which have gained a ...
Jiaochan Hu +5 more
doaj +1 more source
Fuzzy spectral and spatial feature integration for classification of nonferrous materials in hyperspectral data [PDF]
, 2009 Hyperspectral data allows the construction of more elaborate models to sample the properties of the nonferrous materials than the standard RGB color representation.
Iriondo, Pedro M. +4 more
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The Future of Hyperspectral Imaging [PDF]
Journal of Imaging, 2019 The Special Issue on hyperspectral imaging (HSI), entitled “The Future of Hyperspectral Imaging”, has published 12 papers. Nine papers are related to specific current research and three more are review contributions: In both cases, the request is to propose those methods or instruments so as to show the future trends of HSI.
openaire +7 more sources
Band Subset Selection for Hyperspectral Image Classification
Remote Sensing, 2018 This paper develops a new approach to band subset selection (BSS) for hyperspectral image classification (HSIC) which selects multiple bands simultaneously as a band subset, referred to as simultaneous multiple band selection (SMMBS), rather than one ...
Chunyan Yu, Meiping Song, Chein-I Chang
doaj +1 more source
A New GPU Implementation of Support Vector Machines for Fast Hyperspectral Image Classification
Remote Sensing, 2020 The storage and processing of remotely sensed hyperspectral images (HSIs) is facing important challenges due to the computational requirements involved in the analysis of these images, characterized by continuous and narrow spectral channels.
Mercedes E. Paoletti +4 more
doaj +1 more source
Compressed hyperspectral sensing [PDF]
SPIE Proceedings, 2015 Acquisition of high dimensional Hyperspectral Imaging (HSI) data using limited dimensionality imaging sensors has led to restricted capabilities designs that hinder the proliferation of HSI. To overcome this limitation, novel HSI architectures strive to minimize the strict requirements of HSI by introducing computation into the acquisition process.
Grigorios Tsagkatakis +1 more
openaire +2 more sources
Implementation strategies for hyperspectral unmixing using Bayesian source separation. [PDF]
, 2010 Positive Source Separation (BPSS) is a useful unsupervised approach for hyperspectral data unmixing, where numerical non-negativity of spectra and abundances has to be ensured, such in remote sensing. Moreover, it is sensible to impose a sum-to-one (full
Moussaoui, Saïd +11 more
core +1 more source
Fusion of Various Band Selection Methods for Hyperspectral Imagery
Remote Sensing, 2019 This paper presents an approach to band selection fusion (BSF) which fuses bands produced by a set of different band selection (BS) methods for a given number of bands to be selected, nBS.
Yulei Wang +3 more
doaj +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 This article proposed a novel spectral-spatial classification framework for hyperspectral image (HSI) through combining collaborative representation (CR) and maximum margin projection (MMP).
Haoyang Yu +6 more
doaj +1 more source