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

Yang Wang; Huanzhang Lu; Xiongming ZhangXu Han

首页> 外文期刊>Optical Engineering >Novel texture feature persistence metric for automatic-target-recognition-directed image compression

【24h】

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

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

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相关主题

摘要

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.

著录项

来源
《Optical Engineering》 |2006年第6期|060502-1-060502-3-0|共3页
作者
Yang Wang; Huanzhang Lu; Xiongming ZhangXu Han;
展开▼
作者单位

National University of Defense Technology ATR State Key Laboratory Changsha 410073 China;

展开▼
收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种英语
中图分类光学仪器;
关键词
ATR-directed image compression; texture feature persistence metric; similarity metric between shapes;

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

摘要

著录项

相关主题

期刊订阅