Segmentation of multispectral high-resolution satellite imagery using log Gabor filters

Abstract

Image segmentation has been recognized as a valuable approach that performs a region-based rather than a pixel-based analysis of high-resolution satellite imagery. A scheme for segmenting the multispectral IKONOS image based on frequency-domain filtering is presented. The frequency spectrum of typical landscape objects is analysed first. The spectrum curves are comparable in logarithmic coordinates rather than in Cartesian coordinates; therefore the Gabor filters are superseded by log Gabor filters to extract the multiscale texture features from panchromatic band. Edge features then are calculated from the pan-sharpened multispectral bands based on the vector field model. Finally, the texture-marked watershed segmentation algorithm is implemented and the segmentation accuracy is assessed. The experimental results show that the developed scheme generated an effective tool for automatic segmentation of multispectral high-resolution satellite imagery and suppressing the over-segmentation problem of watershed transform.

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Acknowledgments

This work is supported by National High Technology Research and Development Program of China (Grant No. 2008AA12Z106) and by National Natural Science Foundation of China (Grant No. 40801166 and 40771137). The authors would like to express their thanks to Professor Fahui Wang of Northern Illinois University, USA for help for the paper. They also wish to thank four anonymous reviewers for valuable suggestions.