Sheng Ding
Faculty of Information Science and Engineering, Nanjing University, Nanjing, China
Mei Yu
Faculty of Information Science and Engineering, Nanjing University, Nanjing, China
Fucui Li
Faculty of Information Science and Engineering, Nanjing University, Nanjing, China
Xin Jin
Faculty of Information Science and Engineering, Nanjing University, Nanjing, China
Yang Song
Faculty of Information Science and Engineering, Nanjing University, Nanjing, China
Gangyi Jiang
Faculty of Information Science and Engineering, Nanjing University, Nanjing, China
ABSTRACT
In this study, a novel Reduced Reference Image Quality Assessment (RR-IQA) metric is proposed based on energy change in wavelet domain. In the first place, features of Gaussian blur images and their general properties in wavelet domain are analyzed, in terms of the corresponding significance they play on the representation of human visual system. Secondly, in accordance with some authoritative literatures, the change of image energy will evoke the change of human visual perceptual quality. Based on this fact, a series of features from Gaussian blur images which embody the change of image energy are extracted. Finally, we fuse these features based on the principal that we exert different importance in accordance with the different impact each individual sub-band plays on the visual perception. As far as the performance of the proposed metric for the Gaussian blur images is concerned, the proposed metric outperforms the state-of-the-art RR-IQA metrics and even two typical full-reference image quality assessment metrics.
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How to cite this article
Sheng Ding, Mei Yu, Fucui Li, Xin Jin, Yang Song and Gangyi Jiang, 2013. Reduced Reference Image Quality Assessment for Gaussian Blur Distortion. Information Technology Journal, 12: 3382-3389.
DOI: 10.3923/itj.2013.3382.3389
URL: https://scialert.net/abstract/?doi=itj.2013.3382.3389
DOI: 10.3923/itj.2013.3382.3389
URL: https://scialert.net/abstract/?doi=itj.2013.3382.3389
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