Novel texture feature persistence metric for automatic-target-recognition-directed image compression

Yang Wang; Huanzhang Lu; Xiongming Zhang; Xu Han

doi:10.1117/1.2208347

1 June 2006 Novel texture feature persistence metric for automatic-target-recognition-directed image compression

Yang Wang, Huanzhang Lu, Xiongming Zhang, Xu Han

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Optical Engineering, Vol. 45, Issue 6, 060502 (June 2006). https://doi.org/10.1117/1.2208347

Abstract

We present a novel texture feature persistence metric for automatic-target-recognition (ATR)-directed image compression based on the similarity between shapes. On the basis of spatial fuzzy representation of shapes, a similarity metric between shapes is proposed. Then the impact of lossy image compression on ATR performance is measured by the similarity between shapes, which are obtained by identical segmentation and edge extraction of the source image and degraded image after compression. Experimental results show that this metric effectively measures the extent to which target texture features are preserved after compression.

©(2006) Society of Photo-Optical Instrumentation Engineers (SPIE)

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Yang Wang, Huanzhang Lu, Xiongming Zhang, and Xu Han "Novel texture feature persistence metric for automatic-target-recognition-directed image compression," Optical Engineering 45(6), 060502 (1 June 2006). https://doi.org/10.1117/1.2208347

Published: 1 June 2006

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