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Advances in Hyperspectral Image Classification: Earth monitoring with statistical learning methods [PDF]
, 2013 Hyperspectral images show similar statistical properties to natural grayscale or color photographic images. However, the classification of hyperspectral images is more challenging because of the very high dimensionality of the pixels and the small number
Benediktsson, Jón Atli +3 more
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Hyperspectral Image Classification Scheme with Boundary Constrain Label Smoothing Based on Block Neighbor [PDF]
Jisuanji gongcheng, 2017 In order to improve the accuracy of hyperspectral image classification,combined with spectral information,neighborhood information and boundary information,this paper proposes a hyperspectral image classification scheme.The method takes the Local Fisher ...
CHEN Shanxue,GUI Chengming,WANG Yining
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Unsupervised spectral sub-feature learning for hyperspectral image classification [PDF]
, 2016 Spectral pixel classification is one of the principal techniques used in hyperspectral image (HSI) analysis. In this article, we propose an unsupervised feature learning method for classification of hyperspectral images.
De Neve, Wesley +4 more
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Naive Gabor Networks for Hyperspectral Image Classification [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2021 Recently, many convolutional neural network (CNN) methods have been designed for hyperspectral image (HSI) classification since CNNs are able to produce good representations of data, which greatly benefits from a huge number of parameters. However, solving such a high-dimensional optimization problem often requires a large amount of training samples in
Chenying Liu +5 more
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IEEE Access, 2020 In order to improve the classification of hyperspectral image(HSI), we propose a novel hyperspectral image classification method based on the comprehensive evaluation model of extreme learning machine(ELM) with the cumulative variation weights(CVW ...
Yuping Yin, Lin Wei
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A fuzzy spectral clustering algorithm for hyperspectral image classification
IET Image Processing, 2021 Spectral clustering is an unsupervised clustering algorithm, and is widely used in the field of pattern recognition and computer vision due to its good clustering performance.
Kang Li +3 more
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Remote Sensing, 2022 Hyperspectral image (HSI) classification is one of the main research contents of hyperspectral technology. Existing HSI classification algorithms that are based on deep learning use a large number of labeled samples to train models to ensure excellent ...
Shuhan Zhang +5 more
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Supervised hyperspectral image classification with rejection
2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2015 Hyperspectral image classification is a challenging problem as obtaining complete and representative training sets is costly, pixels can belong to unknown classes, and it is generally an ill-posed problem. The need to achieve high classification accuracy may surpass the need to classify the entire image.
Filipe Condessa +2 more
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Classification Endmember Selection with Multi-Temporal Hyperspectral Data
Remote Sensing, 2020 In hyperspectral image classification, so-called spectral endmembers are used as reference data. These endmembers are either extracted from an image or taken from another source.
Tingxuan Jiang +2 more
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A CNN with noise inclined module and denoise framework for hyperspectral image classification
IET Image Processing, 2023 Deep Neural Networks have been successfully applied in hyperspectral image classification. However, most of prior works adopt general deep architectures while ignore the intrinsic structure of the hyperspectral image, such as the physical noise ...
Zhiqiang Gong +5 more
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