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Multi-resolution and multi-spectral image fusion for urban object extraction

A new approach for object extraction from high-resolution satellite images is presented in this paper. The new approach integrates image fusion, multi-spectral classification, feature extraction and feature segmentation into the object extraction of high-resolution satellite images. Both spectral information from multispectral (MS) images and spatial information from panchromatic (Pan) images are utilized for the extraction to improve accuracies. This paper mainly concentrates on road extraction from QuickBird MS and Pan images using the proposed approach. Experiments of road extraction with QuichBird MS and Pan images demonstrate that the proposed approach is effective. The completeness and correctness of road network extraction reaches 0.95, significantly higher than those of other existing road extraction methods.