Results 21 to 30 of about 32,344 (307)
Quality criteria benchmark for hyperspectral imagery [PDF]
, 2005 Hyperspectral data appear to be of a growing interest over the past few years. However, applications for hyperspectral data are still in their infancy as handling the significant size of the data presents a challenge for the user community.
Christophe, Emmanuel +2 more
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Hyperspectral Image Database Query Based on Big Data Analysis Technology [PDF]
E3S Web of Conferences, 2021 In this paper, we extract spectral image features from a hyperspectral image database, and use big data technology to classify spectra hierarchically, to achieve the purpose of efficient database matching.
Qi Beixun
doaj +1 more source
Hyperspectral image unmixing using a multiresolution sticky HDP [PDF]
, 2012 This paper is concerned with joint Bayesian endmember extraction and linear unmixing of hyperspectral images using a spatial prior on the abundance vectors.We propose a generative model for hyperspectral images in which the abundances are sampled from a ...
Hero, Alfred O. +3 more
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Adaptive Markov random fields for joint unmixing and segmentation of hyperspectral image [PDF]
, 2013 Linear spectral unmixing is a challenging problem in hyperspectral imaging that consists of decomposing an observed pixel into a linear combination of pure spectra (or endmembers) with their corresponding proportions (or abundances). Endmember extraction
Eches, Olivier +3 more
core +1 more source
SICE Journal of Control, Measurement, and System Integration, 2022 Recently, the utilization of hyperspectral images containing several hundred wavelength information has been increasing in various fields. If a hyperspectral image can be estimated from a low-cost RGB image that has only R, G, and B wavelength ...
Ryoji Sato +3 more
doaj +1 more source
Hyperspectral image compression : adapting SPIHT and EZW to Anisotropic 3-D Wavelet Coding [PDF]
, 2008 Hyperspectral images present some specific characteristics that should be used by an efficient compression system. In compression, wavelets have shown a good adaptability to a wide range of data, while being of reasonable complexity.
Christophe, Emmanuel +2 more
core +1 more source
Nonlinear unmixing of hyperspectral images: Models and algorithms [PDF]
, 2013 When considering the problem of unmixing hyperspectral images, most of the literature in the geoscience and image processing areas relies on the widely used linear mixing model (LMM).
McLaughlin, Stephen; id_orcid +14 more
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Spectral-spatial multi-layer perceptron network for hyperspectral image land cover classification
European Journal of Remote Sensing, 2022 This paper proposes a novel spectral-spatial multi-layer perceptron network for hyperspectral image land cover classification. Current deep learning-based methods have limitations in spectral and spatial feature representation of hyperspectral images ...
Xiong Tan, Zhixiang Xue
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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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MORPHOLOGICAL SEGMENTATION OF HYPERSPECTRAL IMAGES
Image Analysis & Stereology, 2011 The present paper develops a general methodology for the morphological segmentation of hyperspectral images, i.e., with an important number of channels. This approach, based on watershed, is composed of a spectral classification to obtain the markers and a vectorial gradient which gives the spatial information. Several alternative gradients are adapted
Noyel, Guillaume +2 more
openaire +7 more sources