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Advances in Intelligent Information Hiding and Multimedia Signal Processing pp 69–76Cite as

Multiple Kernel-Learning Based Hyperspectral Data Classification

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 64))

Abstract

Hyperspectral remote sensing based oil and gas exploration technology aims to extract the related information of oil and gas, to achieve the target characteristics of underground oil and gas exploration and recognition through remote sensing data processing and analysis. The rapid development of hyperspectral remote sensing technology bring the accurate detection of surface reflectance spectrum, to increase the success possibility and reduce the cost of oil and gas exploration. The increasing spectral and space resolution of hyperspectral remote sensing bring a large size of data for two problems in the practical satellite platform-based imagery processing system. The bandwidth of the communication channel limits the transmission of the full hyperspectral image data for the further processing and analysis on the ground for the oil and gas exploration. The preprocessing of hyperspectral sensing data is a feasible way through machine learning-based data analysis technology, to produce one image from the full band of hyperspectral images through classifying the spectrum curve of each pixel according to the spectrum data of oil and gas. In this paper, we present the satellite platform based kernel machine-based system for oil and gas exploration based on hyperspectral remote sensing data.

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Authors and Affiliations

  1. Department of Automatic Test and Control, Harbin Institute of Technology, No 92 XIDAZHI Street, 150001, Harbin, China

    Wei Gao & Yu Peng

Authors
  1. Wei Gao
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  2. Yu Peng
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Correspondence to Wei Gao .

Editor information

Editors and Affiliations

  1. National Kaohsiung University of Applied Sciences, Fujian, China

    Jeng-Shyang Pan

  2. College of Information Science and Engin, Fujiang University of Technology College of Information Science and Engin, Fujian, China

    Pei-Wei Tsai

  3. National University of Kaohsiung , Kaohsiung, Taiwan

    Hsiang-Cheh Huang

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Gao, W., Peng, Y. (2017). Multiple Kernel-Learning Based Hyperspectral Data Classification. In: Pan, JS., Tsai, PW., Huang, HC. (eds) Advances in Intelligent Information Hiding and Multimedia Signal Processing. Smart Innovation, Systems and Technologies, vol 64. Springer, Cham. https://doi.org/10.1007/978-3-319-50212-0_9

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  • DOI: https://doi.org/10.1007/978-3-319-50212-0_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50211-3

  • Online ISBN: 978-3-319-50212-0

  • eBook Packages: EngineeringEngineering (R0)

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