Color image quality assessment based on structural features

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Rahmaniani Gona; Mansouri Azadeh

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Journal: MACHINE VISION AND IMAGE PROCESSING Year:2020 | Volume:7 | Issue:1 Page(s): 17-28

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Information Journal Paper

Title

Color image quality assessment based on structural features

Author(s)

Rahmaniani Gona | Mansouri Azadeh | Issue Writer Certificate

Keywords

image quality assessment (IQA)

HVS

Abstract

The aim of digital image quality assessment is to provide a model predicting the human judGMents of viewing scenes. In this paper, a color image quality measure is presented in which a combination of three components including gradient magnitude, phase congruency and visual saliency is utilized for a better prediction. This combination is designed based on the fact that the human visual system extracts the low-level image features. The phase congruency and visual saliency provide robust and contrast invariant structural information of the viewing scene. On the other hand, gradient magnitude captures all changes including the local contrast. Combing these three features can enhance the assessment of local quality. In order to obtain a single measure, the visual saliency is employed in the pooling phase. The experimental results demonstrate that the proposed algorithm can effectively evaluate natural images quality in a consistent manner with the human visual perception.

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APA: Copy

Rahmaniani, Gona, & Mansouri, Azadeh. (2020). Color image quality assessment based on structural features. MACHINE VISION AND IMAGE PROCESSING, 7(1 ), 17-28. SID. https://sid.ir/paper/360866/en

Vancouver: Copy

Rahmaniani Gona, Mansouri Azadeh. Color image quality assessment based on structural features. MACHINE VISION AND IMAGE PROCESSING[Internet]. 2020;7(1 ):17-28. Available from: https://sid.ir/paper/360866/en

IEEE: Copy

Gona Rahmaniani, and Azadeh Mansouri, “Color image quality assessment based on structural features,” MACHINE VISION AND IMAGE PROCESSING, vol. 7, no. 1 , pp. 17–28, 2020, [Online]. Available: https://sid.ir/paper/360866/en

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