Uttam Kumar1, 2, Anindita Dasgupta3, Chiranjit Mukhopadhyay1, N. V. Joshi3, and T. V. Ramachandra2, 3, 4, *
1Department of Management Studies, 2Centre for Sustainable Technologies,
3Centre for Ecological Sciences, 4Centre for infrastructure, Sustainable Transport and Urban Planning,
Indian Institute of Science, Bangalore -560012, India
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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).

Keywords: image fusion, multi-sensor; multi-spectral, IKONOS


PAN Panchromatic
MS Multi-spectral
HSR High spatial resolution
LSR Low spatial resolution
COS Component Substitution
LMVM Local Mean and Variance Matching
IHS Intensity Hue Saturation
FFT Fast Fourier Transform
LP Low Pass
HP High Pass
SF Smoothing Filter
GLP Generalised Laplacian Pyramid
LR Local Regression
SVHC Simulateur de la Vision Humaine des Couleurs
SVR Synthetic Variable Ratio
CC Correlation Coefficient
UIQI Universal Image Quality Index
R-G-B Red-Green-Blue
NIR Near Infra Red
FCC False colour composite
BT Brovey Transform
HPF High Pass Filtering
HPM High Pass Modulation
PCA Principal Component Analysis
ATW À Trous Algorithm-Based Wavelet Transform
MRAIM Multiresolution Analysis-Based Intensity Modulation
GS Gram Schmidt
LMM Local Mean Matching
IRS Indian Remote Sensing Satellite
MRA Modulation and Multi-resolution Analysis
UNB University of New Brunswick
Citation: Uttam Kumar, Anindita Dasgupta, Chiranjit Mukhopadhyay, N. V. Joshi and T. V. Ramachandra, 2011. Comparison of 10 Multi-Sensor Image Fusion Paradigms for IKONOS Images., International Journal of Research and Reviews in Computer Science (IJRRCS), Vol. 2, No. 1, March 2011, 40–47.