Recognition method of multi-feature fusion based on D-S evidence theory in SAR image

doi:10.6046/gtzyyg.2013.02.07

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Abstract In view of the low accuracy of the single feature-based method for target recognition in SAR image, a multi-feature decision-making level fusion method based on SVM and D-S evidence theory was proposed.After a series of image processing, the texture feature, Hu invariant moments feature and peek feature were extracted from the target image. Then the targets were classified according to each type of features utilizing SVM, and the results were used as evidence to construct the basic probability assignment. Conclusively, D-S combination rule of evidence was used to achieve fusion, and final recognition results were given by classification thresholds. The method is used for recognizing three-class targets in MSTAR database, and the recognition rate arrives at 95.5%. Experimental result shows that the method is effective for SAR images target recognition.

Keywords extraction of remote sensing alteration information 2D scatter plot structural analysis in spectral space

TP751.1

Issue Date: 28 April 2013

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	ZHANG Yuanfei
	YUAN Jiming
	YANG Zian
	LYU Weiyan
	ZHANG Siying

Cite this article:

ZHANG Yuanfei,YUAN Jiming,YANG Zian, et al. Recognition method of multi-feature fusion based on D-S evidence theory in SAR image[J]. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(2): 37-41.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2013.02.07 OR https://www.gtzyyg.com/EN/Y2013/V25/I2/37

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