Comparative Study on Classification of Remote Sensing Image by Support Vector Machine

Abstract:

In this paper, the TM image of Landsat-5 was used for classification by the method of support vector machine (SVM). The results and precisions of classification were compared between the different parameter combinations. Further more, precisions are compared between the SVM and traditional algorithm. The results indicate that SVM classification algorithm has the advantage of broad parameters range, without prior knowledge of image and samples. The precision of SVM algorithm is much higher than traditional algorithm, especially adapt to the area without in situ measurement.

• Periodical: Advanced Materials Research (Volume 773)
• Pages: 893-898
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.773.893
• Online since: September 2013
• Authors: Yong Xu, Chang Chun Cheng, Xiao Ming Wang, Meng Qi Mao, Chang Jing Zhang
• Keywords: Remote Sensing, SVM Classification, TM Image

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