To provide a convincing proof that a new method is better than the state of the art, computer graphics projects are often accompanied by user studies, in which a group of observers rank or rate results of several algorithms. Such user studies, known as subjective image quality assessment experiments, can be very time‐consuming and do not guarantee to produce conclusive results. This paper is intended to help design efficient and rigorous quality assessment experiments and emphasise the key aspects of the results analysis. To promote good standards of data analysis, we review the major methods for data analysis, such as establishing confidence intervals, statistical testing and retrospective power analysis. Two methods of visualising ranking results together with the meaningful information about the statistical and practical significance are explored. Finally, we compare four most prominent subjective quality assessment methods: single‐stimulus, double‐stimulus, forced‐choice pairwise comparison and similarity judgements. We conclude that the forced‐choice pairwise comparison method results in the smallest measurement variance and thus produces the most accurate results. This method is also the most time‐efficient, assuming a moderate number of compared conditions.

Tone mapping algorithms offer sophisticated methods for mapping a real-world luminance range to the luminance range of the output medium but they often cause changes in color appearance. In this work we conduct a series of subjective appearance matching experiments to measure the change in image colorfulness after contrast compression and enhancement. The results indicate that the relation between contrast compression and the color saturation correction that matches color appearance is non-linear and smaller color correction is required for small change of contrast. We demonstrate that the relation cannot be fully explained by color appearance models. We propose color correction formulas that can be used with existing tone mapping algorithms. We extend existing global and local tone mapping operators and show that the proposed color correction formulas can preserve original image colors after tone scale manipulation.

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