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Spectral Content Characterization for Efficient Image Detection Algorithm Design

Abstract

This paper presents spectral characterization for efficient image detection using hyperspectral processing techniques. We investigate the relationship between the number of used bands and the performance of the detection process in order to find the optimal number of band reductions. The band reduction significantly reduces computation and implementation complexity of the algorithms. Specifically, we define and characterize the contribution coefficient for each band. Based on the coefficients, we heuristically select the required minimum bands for the detection process. We have shown that the small number of bands is efficient for effective detection. The proposed algorithm is suitable for low-complexity and real-time applications.

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Correspondence to Kyoung-Su Park.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://doi.org/creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Park, K., Hong, S., Park, P. et al. Spectral Content Characterization for Efficient Image Detection Algorithm Design. EURASIP J. Adv. Signal Process. 2007, 082874 (2007). https://doi.org/10.1155/2007/82874

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Keywords

  • Information Technology
  • Quantum Information
  • Optimal Number
  • Detection Algorithm
  • Processing Technique