Enhancement of human visual perception-based image quality analyzer for assessment of contrast enhancement methods

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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.

Original languageEnglish
Pages (from-to)41-47
Number of pages7
JournalInternational Arab Journal of Information Technology
Volume16
Issue number1
Publication statusPublished - Jan 2019

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Image quality
Tuning
Image texture
Mean square error
Luminance
Computational complexity
Entropy
Sampling
Processing

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

Cite this

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title = "Enhancement of human visual perception-based image quality analyzer for assessment of contrast enhancement methods",
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.",
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