Enhancement of Human Visual Perception-Based
Image Quality Analyzer for Assessment of Contrast
Enhancement Methods
Soong Chen1, Tiagrajah
Janahiraman2, and Azizah Suliman1
1College of
Computer Science and Information Technology, Universiti Tenaga Nasional, Malaysia
2College
of Engineering, Universiti Tenaga Nasional, Malaysia
Abstract: Prior to this work, Human Visual Perception (HVP)
-based Image Quality Analyzer (IQA) has been proposed. The HVP-based IQA
correlates with human judgment better than the existing IQAs which are commonly
used for the assessment of contrast enhancement techniques. This paper
highlights the shortcomings of the HVP-based IQA such as high computational
complexity, excessive (six) threshold parameter tuning and high performance
sensitivity to the change in the threshold parameters’ value. In order to
overcome the aforementioned problems, this paper proposes several enhancements such
as replacement of local entropy with edge magnitude in sub-image texture
analysis, down-sampling of image spatial resolution, removal of luminance
masking and incorporation of famous Weber-Fechner Law on human perception. The
enhanced HVP-based IQA requires far less computation (>189 times lesser)
while still showing excellent correlation (Pearson Correlation Coefficient, PCC
> 0.90, Root Mean Square Error, RMSE<0.3410) with human judgment.
Besides, it requires fewer (two) threshold parameter tuning while maintaining
consistent performance across wide range of threshold parameters’ value, making
it feasible for real-time video processing.
Keywords: Contrast enhancement, histogram
equalization, image quality, noise, weber fechner.
