Representative Band Selection for Hyperspectral Image Classification
ISPRS International Journal of Geo-Information, 2018 The high dimensionality of hyperspectral images (HSIs) brings great difficulty for their later data processing. Band selection, as a commonly used dimension reduction technique, is the selection of optimal band combinations from the original bands, while
Fuding Xie +3 more
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EXTRACTION OF OPTIMAL SPECTRAL BANDS USING HIERARCHICAL BAND MERGING OUT OF HYPERSPECTRAL DATA [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015 Spectral optimization consists in identifying the most relevant band subset for a specific application. It is a way to reduce hyperspectral data huge dimensionality and can be applied to design specific superspectral sensors dedicated to specific land ...
A. Le Bris +3 more
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Hyperspectral imagery visualization using band selection
2012 4th Workshop on Hyperspectral Image and Signal Processing (WHISPERS), 2012 This paper investigates hyperspectral image display based on selection of three spectral channels to build a red-green-blue (RGB) composite. A series of band selection algorithms are implemented and compared for this purpose. In particular, three color composition schemes based on visualization-oriented spectral segmentations are proposed.
Hongjun Su, Qian Du, Peijun Du
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Mixed-Noise Band Selection for Hyperspectral Images
IEEE Access, 2020 Hyperspectral images (HSIs) with abundant spectral information are generally susceptible to various types of noise, such as Gaussian noise and stripe noise.
Zhen Li, Chenwei Deng, Yun Huang
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Customizing kernel functions for SVM-based hyperspectral image classification [PDF]
, 2008 Previous research applying kernel methods such as support vector machines (SVMs) to hyperspectral image classification has achieved performance competitive with the best available algorithms.
Baofeng Guo +4 more
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Exploiting Structural Complexity for Robust and Rapid Hyperspectral Imaging [PDF]
, 2013 This paper presents several strategies for spectral de-noising of hyperspectral images and hypercube reconstruction from a limited number of tomographic measurements.
Aeron, Shuchin +2 more
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Effect of Denoising in Band Selection for Regression Tasks in Hyperspectral Datasets [PDF]
, 2013 This paper presents a comparative analysis of six band selection methods applied to hyperspectral datasets for biophysical variable estimation problems, where the effect of denoising on band selection performance has also been analyzed. In particular,
Bioucas-Dias, José +4 more
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Unsupervised Band Selection of Hyperspectral Images via Multi-Dictionary Sparse Representation
IEEE Access, 2018 Band selection is a direct and effective method to reduce the spectral dimension, which is one of popular topics in hyperspectral remote sensing. Recently, a number of methods were proposed to deal with the band selection problem.
Fei Li, Pingping Zhang, Lu Huchuan
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A novel semi-fragile forensic watermarking scheme for remote sensing images [PDF]
, 2011 Peer-reviewedA semi-fragile watermarking scheme for multiple band images is presented. We propose to embed a mark into remote sensing images applying a tree structured vector quantization approach to the pixel signatures, instead of processing each band ...
Aiazzi B. +24 more
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Hyperspectral classification of Cyperus esculentus clones and morphologically similar weeds [PDF]
, 2020 Cyperus esculentus (yellow nutsedge) is one of the world's worst weeds as it can cause great damage to crops and crop production. To eradicate C. esculentus, early detection is key-a challenging task as it is often confused with other Cyperaceae and ...
Cool, Simon R. +4 more
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