Spectral Content Characterization for Efficient Image Detection Algorithm Design. (28th March 2007)

• Record Type: Journal Article
• Authors: Park Park, Kyoung-Su Kyoung-Su; Hong Hong, Sangjin Sangjin; Park Park, Peom Peom; Cho Cho, We-Duke We-Duke
• Other Names: Kuo Kuo C.-C. Jay C.-C. Jay Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2007(2007)
• Publication Date: 2007-03-28
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2007/82874
• Languages: English
• ISSNs: 1687-6172

Abstract

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.