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Perceptually-based Comparison of Image Similarity Metrics

dc.date.accessioned2004-10-20T21:03:39Z
dc.date.accessioned2018-11-24T10:23:27Z
dc.date.available2004-10-20T21:03:39Z
dc.date.available2018-11-24T10:23:27Z
dc.date.issued2001-07-01en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/7235
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/1721.1/7235
dc.description.abstractThe image comparison operation ??sessing how well one image matches another ??rms a critical component of many image analysis systems and models of human visual processing. Two norms used commonly for this purpose are L1 and L2, which are specific instances of the Minkowski metric. However, there is often not a principled reason for selecting one norm over the other. One way to address this problem is by examining whether one metric better captures the perceptual notion of image similarity than the other. With this goal, we examined perceptual preferences for images retrieved on the basis of the L1 versus the L2 norm. These images were either small fragments without recognizable content, or larger patterns with recognizable content created via vector quantization. In both conditions the subjects showed a consistent preference for images matched using the L1 metric. These results suggest that, in the domain of natural images of the kind we have used, the L1 metric may better capture human notions of image similarity.en_US
dc.format.extent13 p.en_US
dc.format.extent9714300 bytes
dc.format.extent2612761 bytes
dc.language.isoen_US
dc.subjectAIen_US
dc.subjectImage matchingen_US
dc.subjectvector quantizationen_US
dc.subjectMinkowski metricen_US
dc.titlePerceptually-based Comparison of Image Similarity Metricsen_US


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