Multi-Scale Classification Based on Remote Sensing

Abstract:

Due to the broadly application of remote sensing imagery, there is an eager need for the classification of objects in the images. The multi-scale classification based on object oriented analysis is not a usual approach for image classification because the users of multi-scale classification do not know how to use the information from multiple scales to do multi-scale classification. Many users rely on some easily accessible tools. nearest neighbour classifier, to do multi-scale classification. The multi-scale classification classifies the images from different scales. The feature values of the object vary from different scales and they may have some trends against scales. These trends may help us to understand multi-scale classification better. This is the scale dependency of features. The difference between multi-scale classification and single-scale classification is not only multiple scales, but also the use of information from different scales. In order to explore the connection between different scales, the research of new features is necessary.

• Periodical: Applied Mechanics and Materials (Volumes 580-583)
• Pages: 2853-2859
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.580-583.2853
• Online since: July 2014
• Authors: Peng Li Li*, Wei Ping Ti, Jia Chun Li
• Keywords: Ecognition Approache, Multi-Scale Classification, Segmentation

References

[1] Atkinson, P. M., & Aplin, P. Spatial variation in land cover and choice of spatial resolution for remote sensing[J]. International Journal of Remote Sensing, 2004, 25(18), 3687-3702.

DOI: 10.1080/01431160310001654383

[2] Benz, U. C., Hofmann, P., Willhauck, G., Lingenfelder, I., & Heynen, M. (2004).

[3] Blaschke, T., & Hay, G. J. Object-oriented image analysis and scale-space theory and methods for modeling and evaluating multiscale landscape structure[J]. International Archives of Photogrammetry and Remote Sensing, 2001 34, 22-29.

[4] Burnett, C. A multi-scale segmentation/object relationship modelling methodology for landscape analysis[J]. Ecological Modelling, 2003168(3), 233-249.

DOI: 10.1016/s0304-3800(03)00139-x

[5] Dragut, L., Tiedec, D., & Levickd, S. R. ESP: a tool to estimate scale parameter for multiresolution image segmentation of remotely sensed data[J]. International Journal of Geographical Information Science, 2010 , (6), 1-13.

DOI: 10.1080/13658810903174803

[6] Esch, T., Thiel, M., Bock, M., Roth, A., & Dech, S. Improvement of Image Segmentation Accuracy Based on Multiscale Optimization Procedure[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2008, 5(3), 463-467.

DOI: 10.1109/lgrs.2008.919622

[7] Liu, D. S., Song, K., Townshend, J. R. G., & Gong, P. Using local transition probability models in Markov random fields for forest change detection[J]. Remote Sensing of Environment, 2008, 112(5), 2222-2231.

DOI: 10.1016/j.rse.2007.10.002

[8] Hall, O., & Hay, G. J. (2003). A multiscale object-specific approach to digital change detection[J]. International Journal of Applied Earth Observation and Geoinformation, 2003, 4(4), 311-327.

DOI: 10.1016/s0303-2434(03)00010-2