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Comparison of 10 Multi-Sensor Image Fusion Paradigms for IKONOS Images

Kumar, Uttam and Dasgupta, Anindita and Mukhopadhyay, Chiranjit and Joshi, NV and Ramachandra, TV (2011) Comparison of 10 Multi-Sensor Image Fusion Paradigms for IKONOS Images. In: International Journal of Research and Reviews in Computer Science, 2 (1). pp. 40-47.

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Fusion of multi-sensor imaging data enables a synergetic interpretation of complementary information obtained by sensors of different spectral ranges. Multi-sensor data of diverse spectral, spatial and temporal resolutions require advanced numerical techniques for analysis and interpretation. This paper reviews ten advanced pixel based image fusion techniques – Component substitution (COS), Local mean and variance matching, Modified IHS (Intensity Hue Saturation), Fast Fourier Transformed-enhanced IHS, Laplacian Pyramid, Local regression, Smoothing filter (SF), Sparkle, SVHC and Synthetic Variable Ratio. The above techniques were tested on IKONOS data (Panchromatic band at 1 m spatial resolution and Multispectral 4 bands at 4 m spatial resolution). Evaluation of the fused results through various accuracy measures, revealed that SF and COS methods produce images closest to corresponding multi-sensor would observe at the highest resolution level (1 m).

Item Type: Journal Article
Additional Information: Copyright of this article belongs to Kohat University of Science and Technology, Pakistan.
Keywords: image fusion;multi-sensor;multi-spectral;IKONOS
Department/Centre: Division of Biological Sciences > Centre for Ecological Sciences
Division of Interdisciplinary Research > Center for Infrastructure, Sustainable Transportation and Urban Planning (CiSTUP)
Division of Interdisciplinary Research > Management Studies
Division of Mechanical Sciences > Centre for Sustainable Technologies (formerly ASTRA)
Depositing User: Ms V Mangala
Date Deposited: 02 Feb 2012 06:41
Last Modified: 02 Feb 2012 06:41
URI: http://eprints.iisc.ac.in/id/eprint/43245

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