A grid-density based technique for finding clusters in satellite image
Pattern Recognition Letters
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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curves are comparable in logarithmic coordinates rather than in Cartesian coordinates; therefore the Gabor filters are superseded by log Gabor filters to extract the multiscale texture features from panchromatic band.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.