高级搜索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

自动目标识别中的图像序列质量评价方法

刁伟鹤 毛峡 常乐

刁伟鹤, 毛峡, 常乐. 自动目标识别中的图像序列质量评价方法[J]. 电子与信息学报, 2010, 32(8): 1779-1785. doi: 10.3724/SP.J.1146.2009.01194
引用本文: 刁伟鹤, 毛峡, 常乐. 自动目标识别中的图像序列质量评价方法[J]. 电子与信息学报, 2010, 32(8): 1779-1785. doi: 10.3724/SP.J.1146.2009.01194
Diao Wei-He, Mao Xia, Chang Le. Quality Estimation of Image Sequence for Automatic Target Recognition[J]. Journal of Electronics & Information Technology, 2010, 32(8): 1779-1785. doi: 10.3724/SP.J.1146.2009.01194
Citation: Diao Wei-He, Mao Xia, Chang Le. Quality Estimation of Image Sequence for Automatic Target Recognition[J]. Journal of Electronics & Information Technology, 2010, 32(8): 1779-1785. doi: 10.3724/SP.J.1146.2009.01194

自动目标识别中的图像序列质量评价方法

doi: 10.3724/SP.J.1146.2009.01194
基金项目: 

航天支撑技术基金和北京航空航天大学博士生创新基金资助课题

Quality Estimation of Image Sequence for Automatic Target Recognition

  • 摘要: 图像质量评价是自动目标识别(ATR)性能评估中的重要组成部分。传统的评价指标如目标信噪比(SNR)等针对的皆是单幅图像,而对于图像序列质量评价的研究尚属空白。针对该问题,该文首次提出了帧间目标变化程度的概念,利用其定量描述图像序列的质量。该指标融合了3部分信息:图像序列中帧间目标区纹理变化的信息,帧间目标大小变化的信息以及帧间目标位置不规律的信息。为验证所提指标的有效性,设计了用于分析帧间目标变化程度和ATR算法实际效果关系的实验,实验用样本为真实的目标图像序列。实验结果表明,帧间目标变化程度与ATR算法性能具有很强的相关性,基本呈现单调关系,是一种有效的图像序列质量评价标准。
  • Li Min and Zhang Gui-lin. Image measures for segmentationalgorithm evaluation of automatic target recognitionsystem[C]. 1st International Symposium on Systems andControl in Aerospace and Astronautics, Harbin, China, 2006:674-679.[2]Edmondson R, Rodgers M, and Banish M, et al.. Single-frameimage processing techniques for low-SNR infraredimagery[C]. Proceeding of SPIE, 2008, 6940: 74-78.[3]Yang L, Zhou Y, Yang J, and Chen L. Variance WIE basedinfrared images processing[J].Electronics Letters.2006,42(15):857-859[4]Clark L G and Vincent V J. Image characterization forautomatic target recognition algorithm evaluations[J].Optical Engineering.1991, 30(2):147-153[5]Trievdi M M and Schirvaikar M V. Quantitativecharacterization of image clutter: problems, progress, andpromises[C][J].proceedings of SPIE.1993, 1967:288-299[6]李敏, 周振华, 张桂林. 自动目标识别算法性能评估中的图像度量研究[J]. 红外与激光工程, 2007, 36(3): 412-416.Li Min, Zhou Zhen-hua, and Zhang Gui-lin. Image measuresin the evaluation of ATR algorithm performance [J]. Infraredand Laser Engineering, 2007, 36(3): 412-416.[7]周川, 张桂林, 陈鸿翔等. 基于试验设计的ATR 算法的性能评估[J]. 华中理工大学学报, 1996, 24(2): 43-45.Zhou Chuan, Zhang Gui-lin, and Chen Hong-xiang.Performance evaluation for ATR algorithms based onexperiments design[J]. Journal of Huazhong University ofScience and Technology, 1996, 24(2): 43-45.[8]Mao Xia and Diao Wei-he. Criterion to evaluate the qualityof infrared small target images[J].Journal of Infrared,Millimeter, and Terahertz Waves.2009, 30(1):56-64[9]常洪花, 张建奇. 基于人眼视觉的红外背景杂波量化技术[J].红外技术, 2004, 26(5): 13-18.Chang Hong-hua and Zhang Jian-qi. Human vision-based onquantitative characterization of IR background clutter [J].Infrared Technology, 2004, 26(5): 13-18.[10]Chang Hong-hua and Zhang Jian-qi. Evaluation of humandetection performance using target structure similarityclutter metrics[J]. Optical Engineering, 2006, 45(9): 41-47.[11]Aviram G and Rotman S R. Analyzing the effect of imagerywavelength on the agreement between various image metricsand human detection performance of targets embedded innatural images[J].Optical Engineering.2008, 40(9):1877-1884[12]He Guo-jing, Zhang Jian-qi, and Chang hong-hua. Cluttermetric based on the Cramer-Rao lower bound on automatictarget recognition[J].Applied Optics.2008, 47(29):5534-5540[13]Rotman S R, Hsu D, Cohen A, Shamay D, and Kowalczyk M.Textural metrics for clutter affecting human targetacquisition[J].Infrared Physics Technology.1996, 37(6):667-674[14]Salem Y B and Nasri S. Texture classification of woven fabricbased on a glcm method and using multiclass support vectormachine[C]. 6th International Multi-Conference on Systems,Signals and Devices, Djerba Tunisia, 2009: 1-8.[15]Wang Jian-hui, Li Feng, Doi Kunio, and Li Qiang. A novelscheme for detection of diffuse lung disease in MDCT by useof statistical texture features[C]. Proceeding of SPIE, 2009,7260: 382-389.[16]杨磊. 复杂背景条件下的红外小目标检测与跟踪算法研究[D].[博士论文], 上海:上海交通大学图像处理与模式识别研究所,2006.Yang Lei. Study on infrared small target detection andtracking algorithm under complex backgrounds [D]. [Ph.D.dissertation], Shanghai: Institude of Image Processing andPattern Recognition, Shanghai Jiao Tong University, 2006.
  • 加载中
计量
  • 文章访问数:  4106
  • HTML全文浏览量:  70
  • PDF下载量:  1078
  • 被引次数: 0
出版历程
  • 收稿日期:  2009-09-08
  • 修回日期:  2009-11-26
  • 刊出日期:  2010-08-19

目录

    /

    返回文章
    返回