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A Study of Spectral Data Processing with Emphasis on Spectral Similarity Measures for Hyperspectral Image Processing

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Soft Computing: Theories and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1053))

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Abstract

In this paper, we have performed extensive research on the various methods which can be employed to develop the libraries for an automatic spectra verification software tool that is capable of classifying spectra in terms of their quality and correctness of the proposed parameter. A key step in building library is to establish the degree of similarity between the various bands of the spectrum, which may originate from various sensors or other data collecting devices. Various methods have been proposed for describing the spectral and structural similarity. Here, we have employed empirical mode decomposition (EMD) followed by spectral similarity measures based on amplitude and shape features. Non-stationary and non-linear series can be processed using the empirical mode decomposition. It is an adaptive time-space analysis method that employs the method of partition. Without leaving the time domain, intrinsic mode functions (IMFs) are created by partitioning the series. Considering the shape and amplitude features of a spectral curve, similarities can be drawn. There are various amplitude similarity measures as well as spectral similarity measures. Amplitude similarity measure methods include the calculation of various distances like Euclidean distance (ED) while spectral similarity measure methods mainly include spectral angle mapper (SAM) and spectral correlation coefficient (SCC) among others.

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Authors and Affiliations

  1. Dr. Akhilesh Das Gupta Institute of Technology and Management, New Delhi, Delhi, 110053, India

    Khushboo, Neeru Bala, Shristee Rawat & Simrandeep Singh

  2. National Institute of Technology Patna, Patna, 800005, India

    Rajeev Arya

Authors
  1. Khushboo
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  2. Neeru Bala
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  3. Shristee Rawat
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  4. Simrandeep Singh
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  5. Rajeev Arya
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Corresponding author

Correspondence to Khushboo .

Editor information

Editors and Affiliations

  1. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Millie Pant

  2. Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University Rajasthan, Jaipur, Rajasthan, India

    Tarun K. Sharma

  3. Department of Instrumentation and Control Engineering, Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, Punjab, India

    Om Prakash Verma

  4. Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, Punjab, India

    Rajesh Singla

  5. Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, Punjab, India

    Afzal Sikander

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Khushboo, Bala, N., Rawat, S., Singh, S., Arya, R. (2020). A Study of Spectral Data Processing with Emphasis on Spectral Similarity Measures for Hyperspectral Image Processing. In: Pant, M., Sharma, T., Verma, O., Singla, R., Sikander, A. (eds) Soft Computing: Theories and Applications. Advances in Intelligent Systems and Computing, vol 1053. Springer, Singapore. https://doi.org/10.1007/978-981-15-0751-9_78

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