By Topic

Visual distortion gauge based on discrimination of noticeable contrast changes

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Weisi Lin ; Inst. for Infocomm Res., Singapore, Singapore ; Li Dong ; Ping Xue

This paper presents a method to discriminate pixel differences according to their impact toward perceived visual quality. Noticeable local contrast changes are formulated firstly since contrast is the basic sensory feature in the human visual system (HVS) perception. The analysis aims at quantifying the actual impact of such changes (further divided into increases and decreases on edges) in different signal contexts. An associated full-reference distortion metric proposed next provides better match with the HVS viewing. Experiments have used two independent visual data sets and the related subjective viewing results, and demonstrated the performance improvement of the proposed metric over the relevant existing ones with various video/images and under diversified test conditions. The proposed metric is particularly effective to visual signal with blurring and luminance fluctuations as the major artifacts, and brings about the fundamental improvement when sharpened image edges are involved.

Published in:

Circuits and Systems for Video Technology, IEEE Transactions on  (Volume:15 ,  Issue: 7 )