The International Arab Journal of Information Technology (IAJIT)

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Enhancement of Human Visual Perception-Based Image Quality Analyzer for Assessment of Contrast

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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[24] Yun S., Kim J., and Kim S., “Image Enhancement using a Fusion Framework of Histogram Equalization and Laplacian Pyramid,” IEEE Transactions on Consumer Electronics, vol. 56, no. 4, pp. 2763-2771, 2010. Enhancement of Human Visual Perception-Based Image Quality Analyzer... 47 Soong Chen is an Associate Professor in the College of Information Technology, Universiti Tenaga Nasional, Putrajaya, Malaysia. He received his BE (1997), M.Sc (2000) and Ph.D (2008) from the Universiti Putra Malaysia, Serdang, Malaysia. His research interest includes image quality assessment, image enhancement, computer vision and image compression. Tiagrajah Janahiraman is a Senior Lecturer in the College of Engineering, Universiti Tenaga Nasional, Putrajaya, Malaysia. He received his B.E (2000) and M.Eng (2002) from Universiti Teknologi Malaysia and Phd in Electrical Engineering from Universiti Tenaga Nasional, Malaysia, in 2012. His research interest includes image processing, face recognition, computer vision and video motion analysis. Azizah Suliman is an Associate Professor at College of Information Technology, Universiti Tenaga Nasional, Malaysia. She received her BCS from Southern Illinois University, USA in 1985, MCS from Universiti Malaya in 1990 and PhD in Computer Science (AI) from Universiti Putra Malaysia in 2011. Her interests includes Image Processing, Soft Computing and Embedded Systems.