No-Reference Image Quality Assessment through SIFT Intensity

Authors

Tongfeng Sun, School of Computer Science and Technology, China University of Mining and Technology, Xuzhou Jiangsu 221116, ChinaFollow
Shifei Ding
Xinzheng Xu

Author Country (or Countries)

China

Abstract

SIFT (Scale Invariant Feature Transform) points are scale-space extreme points, representing local minutiae structure features in the Gaussian scale space. SIFT intensity, as a novel no-reference metric, is feasible to assess various common distortions without the access to reference images. The metric introduces image preprocessing: neighborhood enhancement through contrast enhancement of adjacent pixels to reduce false SIFT points triggered by random signals; double-size image magnification through linear interpolation to amplify distortion effects to improve its sensitivity to image quality. SIFT intensity is defined as the number of SIFT points in a unit region and is calculated based on the first octave of the difference-of-Gaussian scale space. Experimental results demonstrate that SIFT intensity is superior to existing classic no-reference metrics and can be used to assess different distortions.

Suggested Reviewers

N/A

Digital Object Identifier (DOI)

http://dx.doi.org/10.12785/amis/080451

Recommended Citation

Sun, Tongfeng; Ding, Shifei; and Xu, Xinzheng (2014) "No-Reference Image Quality Assessment through SIFT Intensity," Applied Mathematics & Information Sciences: Vol. 08: Iss. 4, Article 51.
DOI: http://dx.doi.org/10.12785/amis/080451
Available at: https://digitalcommons.aaru.edu.jo/amis/vol08/iss4/51