Tone mapping operators (TMO) are pivotal in rendering High Dynamic Range (HDR) content on limited dynamic range media. Analysing the quality of tone mapped images depends on several objective factors and a combination of several subjective factors like aesthetics, fidelity etc. Objective Image quality assessment (IQA) metrics are often used to evaluate TMO quality but they do not always reflect the ground truth. A robust alternative to objective IQA metrics is subjective quality assessment. Although, subjective experiments provide accurate results, they can be time-consuming and expensive to conduct. Over the last decade, crowdsourcing experiments have become more popular for collecting large amount of data within a shorter period of time for a lesser cost. Although they provide more data requiring less resources, lack of controlled environment for the experiment results in noisy data. In this work1, we propose a comprehensive analysis of crowdsourcing experiments with two different groups of participants. Our contributions include a comparative study and a collection of methods to detect unreliable participants in crowdsourcing experiments in a TMO quality evaluation scenario. These methods can be utilized by the scientific community to increase the reliability of the gathered data.
This study focused on suggesting an intelligible index for evaluating gloss degrees of printed images.Psychophysical evaluation of image-clarity was performed for various kinds of paper surfaces. Additionally, cluster analysis was performed for classifying the evaluated values. As results, we found that image-clarity on a printed image and paper can be classified into 4 main categories, and quantitatively clarified that 3 main kinds of paper can be the intelligible index to describe gloss degrees of printed image . Furthermore, extent , in which observers cannot recognize differences of image-clarity, has been shown, and this result is expected to be a useful guide for determining conditions of printers from gloss quality point of view.
This paper presents a study on Quality of Experience (QoE) evaluation of 3D objects in Mixed Reality (MR) scenarios. In particular, a subjective test was performed with Microsoft HoloLens, considering different degradations affecting the geometry and texture of the content. Apart from the analysis of the perceptual effects of these artifacts, given the need for recommendations for subjective assessment of immersive media, this study was also aimed at: 1) checking the appropriateness of a single stimulus methodology (ACR-HR) for these scenarios where observers have less references than with traditional media, and 2) analyzing the possible impact of environment lighting conditions on the quality evaluation of 3D objects in mixed reality (MR), and 3) benchmark state-of-the-art objective metrics in this context. The subjective results provide insights for recommendations for subjective testing in MR/AR, showing that ACR-HR can be used in similar QoE tests and reflecting the influence among the lighting conditions, the content characteristics, and the type of degradations. The objective results show an acceptable performance of perceptual metrics for geometry quantization artifacts and point out the need of further research on metrics covering both geometry and texture compression degradations.