NDLI: Retina model inspired image quality assessment

Content Provider	IEEE Xplore Digital Library
Author	Guangtao Zhai Kaup, A. Jia Wang Xiaokang Yang
Copyright Year	2013
Description	Author affiliation: Multimedia Comm. & Signal Process., Friedrich-Alexander-Univ., Erlangen, Germany (Kaup, A.) \|\| Inst. of Image Comm. & Infor. Process., Shanghai Jiao Tong Univ., Shanghai, China (Guangtao Zhai; Jia Wang; Xiaokang Yang)
Abstract	We proposed in this paper a retina model based approach for image quality assessment. The retinal model is consisted of an optical modulation transfer module and an adaptive low-pass filtering module. We treat the model as a black box and design the adaptive filter using an information theoretical approach. Since the information rate of visual signals is far beyond the processing power of the human visual system, there must be an effective data reduction stage in human visual brain. Therefore, the underlying assumption for the retina model is that the retina reduces the data amount of the visual scene while retaining as much useful information as possible. For full reference image quality assessment, the original and distorted images pass through the retinal filter before some kind of distance is calculated between the images. Retina filtering can serve as a general preprocessing stage for most existing image quality metrics. We show in this paper that retina model based MSE/PSNR, though being straightforward, has already state of the art performance on several image quality databases.
Starting Page	1
Ending Page	6
File Size	2977174
Page Count	6
File Format	PDF
e-ISBN	9781479902903
DOI	10.1109/VCIP.2013.6706367
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-11-17
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Measurement Image quality Visualization Adaptation models Mean Squared Error Noise Peak Signal to Noise Ratio Retina Brain modeling Human Visual System Image Quality assessment Retinal Model
Content Type	Text
Resource Type	Article

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