NDLI: A No-Reference Texture Regularity Metric Based on Visual Saliency

Content Provider	IEEE Xplore Digital Library
Author	Varadarajan, S. Karam, L.J.
Copyright Year	1992
Abstract	This paper presents a no-reference perceptual metric that quantifies the degree of perceived regularity in textures. The metric is based on the similarity of visual attention (VA) of the textural primitives and the periodic spatial distribution of foveated fixation regions throughout the image. A ground-truth eye-tracking database for textures is also generated as part of this paper and is used to evaluate the performance of the most popular VA models. Using the saliency map generated by the best VA model, the proposed texture regularity metric is computed. It is shown through subjective testing that the proposed metric has a strong correlation with the mean opinion score for the perceived regularity of textures. The proposed texture regularity metric can be used to improve the quality and performance of many image processing applications like texture synthesis, texture compression, and content-based image retrieval.
Sponsorship	IEEE Signal Processing Society
Page Count	13
File Size	3707286
Starting Page	2784
Ending Page	2796
File Format	PDF
ISSN	10577149
Volume Number	24
Issue Number	9
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Measurement Visualization Computational modeling Correlation Image coding Image retrieval Image Quality Assessment Visual Attention Texture Analysis Randomness image quality assessment Visual attention texture analysis randomness
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

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