Digital Image Processing

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Blind Image Quality Assessment for Facial Images:The Texture Histogram and NSS Approach


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1 Mohaghegh Ardabil University, Ardabil, Iran, Islamic Republic of
     

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We develop an algorithm for blind facial image quality assessment using the texture descriptors of the histogram locally and any of the extracted features in blinds-II in the DCT domain. This paper proposes a quality assessment algorithm based on the extracted features from the important blocks in the distorted facial image, and then these features are used in a simple approach to predict quality scores. Experimental results are shown to correlate highly with human’s judgments of quality.


Keywords

No Reference Image Quality Assessment (Nr-IQA), Texture Descriptors of the Histogram, Natural Scene Statistics (NSS), Facial Images, Differential Mean Opinion Score (DMOS), Human Vision System (HVS).
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  • Blind Image Quality Assessment for Facial Images:The Texture Histogram and NSS Approach

Abstract Views: 282  |  PDF Views: 4

Authors

Zhila Azimzadeh
Mohaghegh Ardabil University, Ardabil, Iran, Islamic Republic of
Mehdi Nooshyar
Mohaghegh Ardabil University, Ardabil, Iran, Islamic Republic of
Majid Khorrami
Mohaghegh Ardabil University, Ardabil, Iran, Islamic Republic of

Abstract


We develop an algorithm for blind facial image quality assessment using the texture descriptors of the histogram locally and any of the extracted features in blinds-II in the DCT domain. This paper proposes a quality assessment algorithm based on the extracted features from the important blocks in the distorted facial image, and then these features are used in a simple approach to predict quality scores. Experimental results are shown to correlate highly with human’s judgments of quality.


Keywords


No Reference Image Quality Assessment (Nr-IQA), Texture Descriptors of the Histogram, Natural Scene Statistics (NSS), Facial Images, Differential Mean Opinion Score (DMOS), Human Vision System (HVS).