A Comparative Investigation of Image Fusion in the Context of Classification |
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| Authors: | Anshu Gupta Vivek Dey |
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| Institution: | (1) Department of Architecture & Planning, MANIT, Bhopal, 462051, India;(2) Btech Civil Engineering, IIT Kanpur, India |
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| Abstract: | Image fusion assists in visual interpretation, mapping, change detection and many other applications. Multispectral and Panchromatic
images are fused to produce images having enhanced spatial and spectral properties. These properties are generally distorted
from original images. The aim of this paper is to identify the effectiveness of the several fusion techniques based on the
distortions and applications. This paper employs seven image fusion techniques namely, Brovey transform, intensity hue saturation,
high pass filter, principle component analysis, UNB Pansharpening, wavelet transform and multiplicative, available in various
commercial image processing software. The data for this study are panchromatic image of Cartosat-1 and multispectral image
of IRS - P6 LISS 4 sensor of study area, Bhopal Municipal Corporation area, M.P. State, India. The effectiveness of image
fusion techniques is determined by quantitative and qualitative assessments. Quantitative assessment is divided into two parts:
1) assessment of fusion techniques by statistical parameters and 2) accuracy assessment of land use maps generated from the
fused images. For part 1, three parameters namely, mean bias, correlation coefficient and Q4 quality index, have been used.
Based on the results of part 1, UNB Pansharpening and wavelet transform are the best among seven fusion techniques. For part
2, Gaussian and Artificial Neural Network classifiers have been used to generate land cover maps. However, the accuracy results
are inconclusive to identify a single best method. Nevertheless, image fusion by wavelet transform has provided best results
in both the sector. Hence, wavelet transform is concluded as the best among selected fusion techniques. |
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