Multiscale image segmentation and its application in image information extraction

Kaimin Sun; Yan Chen; Deren Li

doi:10.1117/12.713250

28 October 2006 Multiscale image segmentation and its application in image information extraction

Kaimin Sun, Yan Chen, Deren Li

Proceedings Volume 6419, Geoinformatics 2006: Remotely Sensed Data and Information; 64191I (2006) https://doi.org/10.1117/12.713250
Event: Geoinformatics 2006: GNSS and Integrated Geospatial Applications, 2006, Wuhan, China

Abstract

The diversity of the spatial scale of landscape raises the requirement of multiscale analysis of remote sensing (RS) images. Usually the first step to analyze remote sensing images is image segmentation, in which the muitiscale effect should be taken into account to achieve satisfactory segmentation results. This paper describes an effective approach to segment remote sensing images in multiscale. Based on the fact that in a specific scale of a remote sensing image the same objects are similar, the image is first segmented in a small scale by uniting the most similar objects. After that, a set of multiscale objects with full topological relationship can be obtained. Based on the set of multiscale objects, the authors explore the application of this approach in object-oriented information extraction from remote sensing images.

Citation Download Citation

Kaimin Sun, Yan Chen, and Deren Li "Multiscale image segmentation and its application in image information extraction", Proc. SPIE 6419, Geoinformatics 2006: Remotely Sensed Data and Information, 64191I (28 October 2006); https://doi.org/10.1117/12.713250

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