Results 31 to 40 of about 11,302,780 (290)
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
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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
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
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Residual component analysis of hyperspectral images - Application to joint nonlinear unmixing and nonlinearity detection [PDF]
, 2014 This paper presents a nonlinear mixing model for joint hyperspectral image unmixing and nonlinearity detection. The proposed model assumes that the pixel reflectances are linear combinations of known pure spectral components corrupted by an additional ...
Altmann, Yoann +10 more
core +1 more source
STACKED LOCAL FEATURE DETECTOR FOR HYPERSPECTRAL IMAGE [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 Images registration is an important task in hyperspectral image processing, while almost all local feature point based image matching algorithm is designed for single band image only and miss the advantage of abundant spectral information.
Z. Yan, Z. Wu
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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
core +1 more source
ICTACT Journal on Image and Video Processing, 2022 Hyperspectral images (HSI) have a wide range of spectral information compared to conventional images. This rich spectral information leads to store more information about the image.
K Priya, K K Rajkumar
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Design and realization of a miniaturized high resolution computed tomography imaging spectrometer [PDF]
EPJ Web of Conferences, 2022 The computed tomography imaging spectrometer (CTIS) is a relatively unknown snapshot hyperspectral camera. It utilizes computational imaging approaches to gain the hyperspectral image from a spatiospectral smeared sensor image.
Amann Simon +4 more
doaj +1 more source
Joint Bayesian Endmember Extraction and Linear Unmixing for Hyperspectral Imagery [PDF]
, 2009 This paper studies a fully Bayesian algorithm for endmember extraction and abundance estimation for hyperspectral imagery. Each pixel of the hyperspectral image is decomposed as a linear combination of pure endmember spectra following the linear mixing ...
Moussaoui, Saïd +10 more
core +1 more source
智慧农业, 2020 With the development of hyperspectral sensor technology and remote sensing data acquisition platform, the application of hyperspectral data is becoming more and more popular in precision agriculture.
Fu Yuanyuan +7 more
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