Satellite Image Segmentation Using Wavelet Transforms Based on Color and Texture Features

Authors:
Ricardo Dutra Silva;Rodrigo Minetto;William Robson Schwartz;Helio Pedrini
Affiliations:
Department of Computer Science, Federal University of Paraná, Curitiba, Brazil 81531-990;Institute of Computing, University of Campinas, Campinas, Brazil 13084-971;Department of Computer Science, University of Maryland, USA 20742-327;Institute of Computing, University of Campinas, Campinas, Brazil 13084-971
Venue:
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
Year:
2008

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Abstract

Image segmentation is a fundamental process in remote sensing applications, whose main purpose is to allow a meaningful discrimination among constituent regions of interest. This work presents a novel image segmentation method based on wavelet transforms for extracting a number of color and texture features from the images. Traditional feature extraction techniques based on individual pixels usually demand high computational cost. To reduce such computational cost, while achieving high-quality results, our approach is composed of two main stages. Initially, the image is decomposed into blocks of pixels and a wavelet transform is applied to each block to identify homogeneous regions of the image, assigning the entire block to a class. A refinement stage is applied to the remaining pixels which belong to blocks marked as heterogenous in the first stage. The developed method, tested on several remote sensing images and compared to a well known image segmentation method, presents high adaptability to image regions.