Publication Type:

Journal Article

Source:

Special Issue in the Journal of Intelligent and Fuzzy Systems, IOS Press, Netherlands, SCOPUS, SCI Indexed 2016 IF:1.261, Volume 32, Issue 4, p.3151-3158 (2017)

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016771557&doi=10.3233%2fJIFS-169258&partnerID=40&md5=4f157587bf2bceff2b5d6a3c0d373771

Keywords:

Fusion rule, Image fusion, Image quality, Image quality metrics, Intelligent systems, M-band wavelets, Pan-sharpening, Remote sensing, Soft computing, Spectroscopy, Weighted fusion

Abstract:

Remote sensing satellites are proficient in taking earth images across various regions in visible part of electromagnetic spectrum. The images can be panchromatic image of a single band, multispectral image of three to seven different bands, and hyperspectral image taken from about 220 contiguous spectral bands. These images are used together or on its own, depending on the significance and usage of the preferred application. Pan-sharpening is one method which is used to improve the quality of a low resolution multispectral image by fusion with a high resolution panchromatic image. This paper proposes a method based on M-band wavelets for the pan-sharpening of a low resolution multispectral image. The method tries to improve the spatial characteristics while preserving the spectral quality of the data. The proposed technique uses weighted fusion rule and average fusion rule. The data used for the experiment were acquired by high resolution optical imagers onboard QuickBird, WorldView-3, WorldView-2 and GeoEye-1. A comparison with existing fusion techniques is done based on image quality metrics and visual interpretation. The experimental results and analysis suggests that the proposed pan-sharpening technique outperforms other compared pre-existing pan-sharpening methods. © 2017-IOS Press and the authors. All rights reserved.

Notes:

cited By 1

Cite this Research Publication

V. V. Pradeep, Sowmya V., and Dr. Soman K. P., “Application of M-band wavelet in pan-sharpening”, Special Issue in the Journal of Intelligent and Fuzzy Systems, IOS Press, Netherlands, vol. 32, no. 4, pp. 3151-3158, 2017.

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