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DSIM: A DisSIMilarity-based image clutter metric for targeting performance
Xu DJ(徐德江); Shi ZL(史泽林)
Department光电信息技术研究室
Source PublicationIEEE Transactions on Image Processing
ISSN1057-7149
2013
Volume22Issue:10Pages:4108-4122
Indexed BySCI ; EI
EI Accession number20133916769263
WOS IDWOS:000324385200032
Contribution Rank1
KeywordImage Clutter Metric Signal-to-clutter Ratio (Scr) Dissimilarity Metric (Dsim) Human Vision Perceptual Dissimilarity Measure (Vpdm) Brain Cognitive Dissimilarity Measure (Bcdm)
AbstractPrevious image clutter metrics were proposed on the thought that clutter was just a perceptual effect, while we identify clutter as both perceptual and cognitive effects. Under this identification, we give a new definition of image clutter metric by analyzing the research results in the fields of visual psychology and psychophysics. According to the definition, we further put forward a DisSIMilarity (DSIM) based image clutter metric, which can also be taken as a kind of HVS-based signal-to-clutter ratio. The earlier image clutter metrics produced limited success in predicting targeting performance mainly since they did not consider brain cognitive characteristics. We develop a brain cognitive dissimilarity measure (BCDM) as a quantitative estimate of the selection weights which are allocated by brain attentional mechanism to affect visual selection processes. A human vision perceptual dissimilarity measure (VPDM), fully embodying vision perceptual properties, is first established between the target and clutter images, and then we utilize the BCDM between the two images as selection weights to pool the VPDM to be a clutter metric, which can be called DSIM metric. The metric is tested in Search-2 dataset provided by TNO Human Factors Research Institute of Netherlands. Error analysis and correlation tests demonstrate that the DSIM metric makes a more significant improvement than previously proposed metrics in predicting 62 observers' targeting performances including detection probability, false alarm probability and search time.
Language英语
WOS HeadingsScience & Technology ; Technology
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS KeywordSTRUCTURAL SIMILARITY ; DETECTION PROBABILITY ; QUALITY ASSESSMENT ; INFRARED IMAGES ; SEARCH ; INFORMATION ; SYSTEMS ; RECOGNITION ; ACQUISITION ; ATTENTION
WOS Research AreaComputer Science ; Engineering
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/12526
Collection光电信息技术研究室
Corresponding AuthorXu DJ(徐德江)
Affiliation1.Graduate University of Chinese Academy of Sciences, Beijing 10049, China
2.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
3.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 100081, China
Recommended Citation
GB/T 7714
Xu DJ,Shi ZL. DSIM: A DisSIMilarity-based image clutter metric for targeting performance[J]. IEEE Transactions on Image Processing,2013,22(10):4108-4122.
APA Xu DJ,&Shi ZL.(2013).DSIM: A DisSIMilarity-based image clutter metric for targeting performance.IEEE Transactions on Image Processing,22(10),4108-4122.
MLA Xu DJ,et al."DSIM: A DisSIMilarity-based image clutter metric for targeting performance".IEEE Transactions on Image Processing 22.10(2013):4108-4122.
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