Objective Quality Assessment of Tone-Mapped Images

• Published in: IEEE transactions on image processing Vol. 22; no. 2; pp. 657 - 667
• Main Authors: Yeganeh, H., Zhou Wang
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.02.2013; Institute of Electrical and Electronics Engineers
• Subjects: Applied sciences; Brightness; Correlation; Detection, estimation, filtering, equalization, prediction; Dynamic range; Exact sciences and technology; High dynamic range image; image fusion; Image processing; image quality assessment; Information, signal and communications theory; naturalness; perceptual image processing; Quality assessment; Sensitivity; Signal and communications theory; Signal processing; Signal, noise; structural similarity; Telecommunications and information theory; tone mapping operator; Visualization; Dynamic response; perceptual image processing; Similarity; Image processing; Objective analysis; Image databank; structural similarity; Timbre; Algorithm; High dynamic range image; Subjective evaluation; Optimization; Image quality; HDR image; Tone mapping; Multiscale method; naturalness; Quality control; image quality assessment; Image fusion; Image evaluation; tone mapping operator
• ISSN: 1057-7149; 1941-0042; 1941-0042
• DOI: 10.1109/TIP.2012.2221725

Tone-mapping operators (TMOs) that convert high dynamic range (HDR) to low dynamic range (LDR) images provide practically useful tools for the visualization of HDR images on standard LDR displays. Different TMOs create different tone-mapped images, and a natural question is which one has the best quality. Without an appropriate quality measure, different TMOs cannot be compared, and further improvement is directionless. Subjective rating may be a reliable evaluation method, but it is expensive and time consuming, and more importantly, is difficult to be embedded into optimization frameworks. Here we propose an objective quality assessment algorithm for tone-mapped images by combining: 1) a multiscale signal fidelity measure on the basis of a modified structural similarity index and 2) a naturalness measure on the basis of intensity statistics of natural images. Validations using independent subject-rated image databases show good correlations between subjective ranking score and the proposed tone-mapped image quality index (TMQI). Furthermore, we demonstrate the extended applications of TMQI using two examples - parameter tuning for TMOs and adaptive fusion of multiple tone-mapped images.