Results 21 to 30 of about 109,457 (327)
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
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A new kernel method for hyperspectral image feature extraction [PDF]
, 2017 Hyperspectral image provides abundant spectral information for remote discrimination of subtle differences in ground covers. However, the increasing spectral dimensions, as well as the information redundancy, make the analysis and interpretation of ...
Gao, Lianru +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
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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
Benediktsson, Jon Atli +3 more
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An Integrative Remote Sensing Application of Stacked Autoencoder for Atmospheric Correction and Cyanobacteria Estimation Using Hyperspectral Imagery [PDF]
, 2020 Hyperspectral image sensing can be used to effectively detect the distribution of harmful cyanobacteria. To accomplish this, physical- and/or model-based simulations have been conducted to perform an atmospheric correction (AC) and an estimation of ...
Baek, Sangsoo +10 more
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Linear vs Nonlinear Extreme Learning Machine for Spectral-Spatial Classification of Hyperspectral Image [PDF]
, 2017 As a new machine learning approach, extreme learning machine (ELM) has received wide attentions due to its good performances. However, when directly applied to the hyperspectral image (HSI) classification, the recognition rate is too low. This is because
Cao, Faxian +4 more
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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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Compressive Hyperspectral Imaging Using Progressive Total Variation [PDF]
, 2014 Compressed Sensing (CS) is suitable for remote acquisition of hyperspectral images for earth observation, since it could exploit the strong spatial and spectral correlations, llowing to simplify the architecture of the onboard sensors. Solutions proposed
Barducci, Alessandro +4 more
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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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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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