Progressive Texture Matching for Earth Observing Satellite Image Database

Content-based indexing of images and videos based on texture features is a powerful mechanism to retrieve images and video scenes. However, the feature extraction process from these images and video is time consuming and is not suitable for interactive query processing. A progressive texture extraction and matching algorithm is proposed and evaluated in this paper. This algorithm takes advantage of the multi-resolution representation of an image generated by the subband coding or the wavelet transformation. Starting at a resolution lower than the full resolution of an image or video, the proposed algorithm performs the feature extraction and matching hierarchically. Only those regions matched to the target template at a lower resolution level will be further compared at a higher resolution. The computation speed of this algorithm is shown to be significantly improved (up to 300%) over conventional algorithms while maintaining the same accuracy.