Spectral content characterization for efficient image detection algorithm design

Authors:
Kyoung-Su Park;Sangjin Hong;Peom Park;We-Duke Cho
Affiliations:
Mobile Systems Design Laboratory, Department of Electrical and Computer Engineering, Stony Brook University-SUNY, Stony Brook, NY;Mobile Systems Design Laboratory, Department of Electrical and Computer Engineering, Stony Brook University-SUNY, Stony Brook, NY;Department of Industrial and Information Systems Engineering, Ajou University, Suwon-Si, South Korea and Humintec Co. Ltd., Suwon-Si, South Korea;Department of Electronics Engineering, College of Information Technology, Ajou University, Suwon-Si, South Korea
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2007

Citing 2
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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.