Preference of Experience in Image Tone-Mapping: Dataset and Framework for Objective Measures Comparison
TL;DR: A subjective experiment attempting to determine users’ preference with respect to these two types of content in two different viewing scenarios—with and without the HDR reference shows that the absence of the reference can significantly influence the subjects' preferences for the natural images, while no significant impact has been found in the case of the synthetic images.
Abstract: The popularity of high dynamic range (HDR) imaging has grown in both academic and private research sectors. Since the native visualization of HDR content still has its limitations, the importance of dynamic range compression (i.e., tone-mapping) is very high. This paper evaluates observers’ preference of experience in context of image tone-mapping. Given the different nature of natural and computer-generated content, the way observers perceive the quality of tone-mapped images can be fundamentally different. In this paper, we describe a subjective experiment attempting to determine users’ preference with respect to these two types of content in two different viewing scenarios—with and without the HDR reference. The results show that the absence of the reference can significantly influence the subjects’ preferences for the natural images, while no significant impact has been found in the case of the synthetic images. Moreover, we introduce a benchmarking framework and compare the performance of selected objective metrics. The resulting dataset and framework are made publicly available to provide a common test bed and methodology for evaluating metrics in the considered scenario.
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TL;DR: Experimental simulation results obtained from two large SCI databases have shown that the proposed GFM model yields a higher consistency with the human perception on the assessment of SCIs but also requires a lower computational complexity, compared with that of classical and state-of-the-art IQA models.
Abstract: In this paper, an accurate and efficient full-reference image quality assessment (IQA) model using the extracted Gabor features, called Gabor feature-based model (GFM), is proposed for conducting objective evaluation of screen content images (SCIs). It is well-known that the Gabor filters are highly consistent with the response of the human visual system (HVS), and the HVS is highly sensitive to the edge information. Based on these facts, the imaginary part of the Gabor filter that has odd symmetry and yields edge detection is exploited to the luminance of the reference and distorted SCI for extracting their Gabor features, respectively. The local similarities of the extracted Gabor features and two chrominance components, recorded in the LMN color space, are then measured independently. Finally, the Gabor-feature pooling strategy is employed to combine these measurements and generate the final evaluation score. Experimental simulation results obtained from two large SCI databases have shown that the proposed GFM model not only yields a higher consistency with the human perception on the assessment of SCIs but also requires a lower computational complexity, compared with that of classical and state-of-the-art IQA models. 1 1 The source code for the proposed GFM will be available at http://smartviplab.org/pubilcations/GFM.html .
93 citations
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...[43]–[45] can not be employed to perform statistical significance test in this work....
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TL;DR: This paper builds a compressed VR image quality (CVIQ) database, and proposes a multi-channel convolution neural network (CNN) for blind 360-degree image quality assessment (MC360IQA), which achieves the best performance among the state-of-art full-reference and no-reference image quality Assessment (IQA) models on the CVIQ database and other available360-degree IQA database.
Abstract: 360-degree images/videos have been dramatically increasing in recent years. The characteristic of omnidirectional-view results in high resolution of 360-degree images/videos, which makes them difficult to be transported and stored. To deal with the problem, video coding technologies are used to compress the omnidirectional content but they will introduce the compression distortion. Therefore, it is important to study how popular coding technologies affect the quality of 360-degree images. In this paper, we present a study on both subjective and objective quality assessment of compressed virtual reality (VR) images. We first build a compressed VR image quality (CVIQ) database including 16 reference images and 528 compressed ones with three prevailing coding technologies. Then, we propose a multi-channel convolution neural network (CNN) for blind 360-degree image quality assessment (MC360IQA). To be consistent with the visual content seen in the VR device, we project each 360-degree image into six viewport images, which are adopted as inputs of the proposed model. MC360IQA consists of two parts, a multi-channel CNN and an image quality regressor. The multi-channel CNN includes six parallel hyper-ResNet34 networks, where the hyper structure is used to incorporate the features from intermediate layers. The image quality regressor fuses the features and regresses them to final scores. The experimental results show that our model achieves the best performance among the state-of-art full-reference (FR) and no-reference (NR) image quality assessment (IQA) models on the CVIQ database and other available 360-degree IQA database.
91 citations
Cites background from "Preference of Experience in Image T..."
...[70]–[73], which evaluates classification abilities of IQA models to distinguish which of the two images is better or of the...
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TL;DR: In this article, screen content, which is often computer-generated, has many characteristics distinctly different from conventional camera-captured natural scene content, and such characteristic differences impose majo...
Abstract: Screen content, which is often computer-generated, has many characteristics distinctly different from conventional camera-captured natural scene content. Such characteristic differences impose majo...
54 citations
TL;DR: The experimental results show that the proposed method can efficiently resist different TMOs and common image attacks, outperforming other existing HDR image watermarking methods.
25 citations
TL;DR: The focus of this contribution is the development of a QoE assessment framework, in line with the latest standardization progress in the field of QOE assessment, for understanding the visual effect of asymmetric and symmetric encoding for immersive media.
Abstract: The assessment of Quality of Experience (QoE) for stereoscopic 3-D video is a challenging task, especially in 3-D video compression and transmission applications. The focus of this contribution is the development of a QoE assessment framework, in line with the latest standardization progress in the field of QoE assessment, for understanding the visual effect of asymmetric and symmetric encoding for immersive media. Asymmetric stereoscopic video coding exploits the binocular suppression of the human vision system by representing one of the two views with a lower quality. This processing, while of limited effects on image quality, may influence the overall QoE. Many studies show that the QoE of immersive media such as 3-DTV can be thought as the combination of the perceived visual quality, the perceived depth quality, the visual fatigue, and visual discomfort. In this paper, we aim at: 1) exploiting the concept of preference of experience and protocols recently standardized for characterizing QoE; 2) conducting a case study using these standardized protocols to investigate the factors involving visual discomfort in stereoscopic video sequences with a focus on binocular rivalry; and 3) presenting the results of subjective experiments performed, by using the perceptual quality and preference of experience assessment protocols, for evaluating the impact of symmetrical, asymmetrical, and alternate coding schemes.
16 citations
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...Preference of Experience (PoE) [15] and employed beyond 3DTV in context such as HDR QoE assessment [16]....
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References
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TL;DR: A nonparametric approach to the analysis of areas under correlated ROC curves is presented, by using the theory on generalized U-statistics to generate an estimated covariance matrix.
Abstract: Methods of evaluating and comparing the performance of diagnostic tests are of increasing importance as new tests are developed and marketed. When a test is based on an observed variable that lies on a continuous or graded scale, an assessment of the overall value of the test can be made through the use of a receiver operating characteristic (ROC) curve. The curve is constructed by varying the cutpoint used to determine which values of the observed variable will be considered abnormal and then plotting the resulting sensitivities against the corresponding false positive rates. When two or more empirical curves are constructed based on tests performed on the same individuals, statistical analysis on differences between curves must take into account the correlated nature of the data. This paper presents a nonparametric approach to the analysis of areas under correlated ROC curves, by using the theory on generalized U-statistics to generate an estimated covariance matrix.
16,496 citations
TL;DR: This work has recently derived a blind IQA model that only makes use of measurable deviations from statistical regularities observed in natural images, without training on human-rated distorted images, and, indeed, without any exposure to distorted images.
Abstract: An important aim of research on the blind image quality assessment (IQA) problem is to devise perceptual models that can predict the quality of distorted images with as little prior knowledge of the images or their distortions as possible. Current state-of-the-art “general purpose” no reference (NR) IQA algorithms require knowledge about anticipated distortions in the form of training examples and corresponding human opinion scores. However we have recently derived a blind IQA model that only makes use of measurable deviations from statistical regularities observed in natural images, without training on human-rated distorted images, and, indeed without any exposure to distorted images. Thus, it is “completely blind.” The new IQA model, which we call the Natural Image Quality Evaluator (NIQE) is based on the construction of a “quality aware” collection of statistical features based on a simple and successful space domain natural scene statistic (NSS) model. These features are derived from a corpus of natural, undistorted images. Experimental results show that the new index delivers performance comparable to top performing NR IQA models that require training on large databases of human opinions of distorted images. A software release is available at http://live.ece.utexas.edu/research/quality/niqe_release.zip.
3,722 citations
"Preference of Experience in Image T..." refers methods in this paper
...Publicly available datasets of HDR images processed by different TMOs including respective subjective scores are mainly restricted to the experiments performed by Čadı́k et al. [5] and Yeganeh and Wang [10]....
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1,992 citations
1,863 citations
"Preference of Experience in Image T..." refers methods in this paper
...For displaying the HDR images, SIM2 HDR47E S 4K display was used, which is a 16-bit, 47-inch, 1080p LCD TV with maximum and minimum displayable luminance of 4000 and 0.03 cd/m2 , respectively....
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01 Jul 2002
TL;DR: The work presented in this paper leverages the time-tested techniques of photographic practice to develop a new tone reproduction operator and uses and extends the techniques developed by Ansel Adams to deal with digital images.
Abstract: A classic photographic task is the mapping of the potentially high dynamic range of real world luminances to the low dynamic range of the photographic print. This tone reproduction problem is also faced by computer graphics practitioners who map digital images to a low dynamic range print or screen. The work presented in this paper leverages the time-tested techniques of photographic practice to develop a new tone reproduction operator. In particular, we use and extend the techniques developed by Ansel Adams to deal with digital images. The resulting algorithm is simple and produces good results for a wide variety of images.
1,708 citations
"Preference of Experience in Image T..." refers result in this paper
...Hence, our studies provide valuable insights towards this goal....
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