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Proceedings Paper

Totally blind image quality assessment evaluator
Author(s): Saifeldeen Abdalmajeed; Jiao Shuhong; Liu Wei
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Paper Abstract

Most general purpose no-reference image quality assessment algorithms need prior knowledge about anticipated distortions and their corresponding human opinion scores. One or more of distortion types may not be available when creating the model. In this paper, we develop a blind/no-reference opinion unaware distortion unaware image quality assessment algorithm based on natural scenes. The proposed approach extracts features in spatial domain for both natural images and distorted image at two scales, where locally normalized luminance values are modeled in two forms: pointwise for single pixels and pair-wise based log-derivative for the relationship of adjacent pixels. Then two sharpness functions are applied whose their outputs represent the extracted features of the proposed approach. Results show that the proposed algorithm correlates well with subjective opinion scores. They also show that the proposed algorithm outperforms the full-reference PSNR and SSIM methods. Not only do the results compete well with the recently developed NIQE model, but also outperform it.

Paper Details

Date Published: 10 January 2014
PDF: 5 pages
Proc. SPIE 9069, Fifth International Conference on Graphic and Image Processing (ICGIP 2013), 90690M (10 January 2014); doi: 10.1117/12.2050200
Show Author Affiliations
Saifeldeen Abdalmajeed, Harbin Engineering Univ. (China)
Jiao Shuhong, Harbin Engineering Univ. (China)
Liu Wei, Beijing Institute of Astronautical System Engineering (China)

Published in SPIE Proceedings Vol. 9069:
Fifth International Conference on Graphic and Image Processing (ICGIP 2013)
Yulin Wang; Xudong Jiang; Ming Yang; David Zhang; Xie Yi, Editor(s)

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