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Optical Engineering • Open Access

Novel texture feature persistence metric for automatic-target-recognition-directed image compression
Author(s): Yang Wang; Huanzhang Lu; Xiongming Zhang; Xu Han

Paper 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.

Paper Details

Date Published: 1 June 2006
PDF: 3 pages
Opt. Eng. 45(6) 060502 doi: 10.1117/1.2208347
Published in: Optical Engineering Volume 45, Issue 6
Show Author Affiliations
Yang Wang, National Univ. of Defense Technology (China)
Huanzhang Lu, National Univ. of Defense Technology (China)
Xiongming Zhang, National Univ. of Defense Technology (China)
Xu Han, Nanjing Univ. of Science & Technology (China)


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