Results 201 to 210 of about 9,650 (249)

Hyperspectral image classification: A benchmark

2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017
Hyperspectral image classification, an astonishing tool to distinguish the land covers in remote sensed hyperspectral images, has been investigated by multiple disciplines such as geoscience, environmental science, mathematics, and computer vision.
Xudong Kang, Shutao Li 0001, Jón Atli Benediktsson   +2 more
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Hyperspectral Image Classification With Background

IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
Background (BKG) is an integral part of an image and has significant effect and impact on hyperspectral image classification (HSIC). Unfortunately, how to address the BKG issue has not received much attention over the past years. This paper investigates this issue by developing a mixed pixel classifier, iterative constrained energy minimization (ICEM ...
Xiao-Di Shang, Meiping Song, Chunyan Yu
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Boosting CNN for Hyperspectral Image Classification

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021
In recent years, deep convolutional neural networks (CNNs) have been widely used for hyperspectral image (HSI) classification. Besides, ensemble learning is a useful way to enhance the classification performance. Therefore, in this study, a new method titled Boosting-CNN is proposed for HSI classification, which fully explored the advantages of deep ...
Haoyu Zhang, Yushi Chen 0002, Xin He 0004, Xingliang Shen   +3 more
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Adapting Kernels for Hyperspectral Image Classification

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021
Despite its great potential in a wide range of human activities, hyperspectral remote sensing imaging (HSI) exhibits several challenges that prevent full exploitation of its data. In particular, land-cover classification based on HSI data suffers significant degradation due to problematic data variability.
Juan Mario Haut, Mercedes Eugenia Paoletti, Rafael Pastor Vargas, Llanos Tobarra, Antonio Robles-Gómez, Roberto Hernández 0001, Eligius M. T. Hendrix, J. Li   +7 more
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A probabilistic method for the classification of hyperspectral images

2016 24th Signal Processing and Communication Application Conference (SIU), 2016
In this study a supervised classification and dimensionality reduction method for hyperspectral images is proposed. For this purpose, using probabilistic principal component analysis (PPCA), dimensionality reduction is performed and a Gaussian mixture model (GMM) is built.
Sezer Kutluk, Koray Kayabol, Aydin Akan
openaire   +2 more sources

Superpixel based classification of hyperspectral images

2015 23nd Signal Processing and Communications Applications Conference (SIU), 2015
Hyperspectral imaging captures a high number of spectrally narrow bands and provides advantages for image analysis applications such as identification and classification in particular. Hyperspectral images contain a large amount of bands. Processing these images causes the operation load substantially.
Cezairlioglu, Kubra, ERTÜRK, SARP, Cakmak, Mehtap   +2 more
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Optimizing wavelets for hyperspectral image classification

2009 IEEE International Geoscience and Remote Sensing Symposium, 2009
This work presents a procedure to optimize a wavelet filter in terms of discrimination capability between the classes characterizing a given hyperspectral remote sensing image. To this end, this procedure estimates the coefficients of the wavelet filter bank by means of a particle swarm optimization (PSO) so that to maximize the average Bhattacharyya ...
A. Daamouche, Melgani, Farid, L. Hamami
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Hyperspectral Image Classification With Adversarial Attack

IEEE Geoscience and Remote Sensing Letters, 2022
The performance of a neural network is highly dependent on the labelled samples. However, the labelled samples are primarily clean, which prevents the network from capturing the features of the samples near the decision boundary. For hyperspectral images (HSIs), high-spectral dimensions and same-spectra foreign matter lead to more boundary samples in ...
Cheng Shi 0002, Yenan Dang, Li Fang, Zhiyong Lv, Minghua Zhao   +4 more
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Hierarchical classification systems for hyperspectral image classification

2007 IEEE International Geoscience and Remote Sensing Symposium, 2007
In this study, we proposed some alternatives for building a binary hierarchical classification (BHC) systems. Two criteria for building the hierarchical tree under the idea of max-cut are addressed and two additional classification architectures based on the constructed trees are also proposed.
Bor-Chen Kuo, Ming-Hung Chi, Jinn-Min Yang, Chin-Wei Yang   +3 more
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Dimensionality reduction in hyperspectral image classification

2004 International Conference on Image Processing, 2004. ICIP '04., 2005
Hyperspectral images provide a vast amount of information about a scene. However, much of that information is redundant as the bands are highly correlated. For computational and data compression reasons, it is desired to reduce the dimensionality of the data set while maintaining good performance in image analysis tasks.
Huiwen Zeng, H. Joel Trussell
openaire   +1 more source