A novel blind image quality assessment metric and its feature selection strategy

Ying Chu; Xuanqin Mou; Wei Hong; Zhen Ji

doi:10.1117/12.2008442

4 February 2013 A novel blind image quality assessment metric and its feature selection strategy

Ying Chu, Xuanqin Mou, Wei Hong, Zhen Ji

Proceedings Volume 8660, Digital Photography IX; 86600F (2013) https://doi.org/10.1117/12.2008442
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States

Abstract

We recently proposed a natural scene statistics based image quality assessment (IQA) metric named STAIND, which extracts nearly independent components from natural image, i.e., the divisive normalization transform (DNT) coefficients, and evaluates perceptual quality of distortion image by measuring the degree of dependency between neighboring DNT coefficients. To improve the performance of STAIND, its feature selection strategy is thoroughly analyzed in this paper. The basic neighbor relationships in STAIND include scale, orientation and space. By analyzing the joint histograms of different neighborships and comparing the IQA model performances of diverse feature combination schemes on the publicly available databases such as LIVE, CSIQ and TID2008, we draw the following conclusions: 1) Spatial neighbor relationship contributes most to the model design, scale neighborship takes second place, and orientation neighbors might introduce negative effects; 2) In spatial domain, second order spatial neighbors are beneficial supplements to first order spatial neighbors; 3) The combined neighborship between the scales, spaces and the introduced spatial parents is very efficient for blind IQA metrics design.

Citation Download Citation

Ying Chu, Xuanqin Mou, Wei Hong, and Zhen Ji "A novel blind image quality assessment metric and its feature selection strategy", Proc. SPIE 8660, Digital Photography IX, 86600F (4 February 2013); https://doi.org/10.1117/12.2008442

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available