Noise reduction for gradient-based multispectral image fusion

Jong Hyun Park, Moon Gi Kang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper, we propose a new noise reduction algorithm for the gradient-based fusion of multispectral images degraded by noise. The gradients resulted mainly from noise are less included in the fusion process than those from salient features according to a minimum mean square error (MMSE) criterion. The selection of appropriate stationary support region for the criterion is studied. Experimental results show that the proposed method is superior to pre- or post-processing methods of noise reduction based on MMSE criteria. The fused result of multispectral iris images is presented for an application to iris recognition.

Original languageEnglish
Title of host publicationProceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2004
EditorsS.J. Ko
Pages185-188
Number of pages4
Publication statusPublished - 2004
EventProceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2004 - Seoul, Korea, Republic of
Duration: 2004 Nov 182004 Nov 19

Publication series

NameProceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2004

Other

OtherProceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2004
CountryKorea, Republic of
CitySeoul
Period04/11/1804/11/19

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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  • Cite this

    Park, J. H., & Kang, M. G. (2004). Noise reduction for gradient-based multispectral image fusion. In S. J. Ko (Ed.), Proceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2004 (pp. 185-188). (Proceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2004).