With the emergence of high-dynamic range (HDR) imaging, the existing visual signal processing systems will need to deal with both HDR and standard dynamic range (SDR) signals. In such systems, computing the objective quality is an important aspect in various optimization processes (e.g., video encoding). To that end, we present a newly calibrated objective method that can tackle both HDR and SDR signals. As it is based on the previously proposed HDR-VDP-2 method, we refer to the newly calibrated metric as HDR-VDP-2.2. Our main contribution is toward improving the frequency-based pooling in HDR-VDP-2 to enhance its objective quality prediction accuracy. We achieve this by formulating and solving a constrained optimization problem and thereby finding the optimal pooling weights. We also carried out extensive cross-validation as well as verified the performance of the new method on independent databases. These indicate clear improvement in prediction accuracy as compared with the default pooling weights. The source codes for HDR-VDP-2.2 are publicly available online for free download and use.

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HDR-VDP-2.2: a calibrated method for objective quality prediction of high-dynamic range and standard images

High dynamic range (HDR) signals fundamentally differ from the traditional low dynamic range (LDR) ones in that pixels are related (proportional) to the physical luminance in the scene (i.e. scene-referred). For that reason, the existing LDR video quality measurement methods may not be directly used for assessing quality in HDR videos. To address that, we present an objective HDR video quality measure (HDR-VQM) based on signal pre-processing, transformation, and subsequent frequency based decomposition. Video quality is then computed based on a spatio-temporal analysis that relates to human eye fixation behavior during video viewing. Consequently, the proposed method does not involve expensive computations related to explicit motion analysis in the HDR video signal, and is therefore computationally tractable. We also verified its prediction performance on a comprehensive, in-house subjective HDR video database with 90 sequences, and it was found to be better than some of the existing methods in terms of correlation with subjective scores (for both across sequence and per sequence cases). A software implementation of the proposed scheme is also made publicly available for free download and use. HighlightsThe paper presents one of the first objective method for high dynamic range video quality estimation.It is based on analysis of short term video segments taking into account human viewing behavior.The method described in the paper would be useful in scenarios where HDR video quality needs to be determined in an HDR video chain study.

Hdr-vqm

Recent advances in high dynamic range (HDR) capture and display technologies have attracted a lot of interest from scientific, professional, and artistic communities. As in any technology, the evaluation of HDR systems in terms of quality of experience is essential. Subjective evaluations are time consuming and expensive, and thus objective quality assessment tools are needed as well. In this paper, we report and analyze the results of an extensive benchmarking of objective quality metrics for HDR image quality assessment. In total, 35 objective metrics were benchmarked on a database of 20 HDR contents encoded with 3 compression algorithms at 4 bit rates, leading to a total of 240 compressed HDR images, using subjective quality scores as ground truth. Performance indexes were computed to assess the accuracy, monotonicity, and consistency of the metric estimation of subjective scores. Statistical analysis was performed on the performance indexes to discriminate small differences between metrics. Results demonstrated that metrics designed for HDR content, i.e., HDR-VDP-2 and HDR-VQM, are the most reliable predictors of perceived quality. Finally, our findings suggested that the performance of most full-reference metrics can be improved by considering non-linearities of the human visual system, while further efforts are necessary to improve performance of no-reference quality metrics for HDR content.

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Benchmarking of objective quality metrics for HDR image quality assessment

Standards play an important role in providing a common set of specifications and allowing inter-operability between devices and systems. Until recently, no standard for high-dynamic-range (HDR) image coding had been adopted by the market, and HDR imaging relies on proprietary and vendor-specific formats which are unsuitable for storage or exchange of such images. To resolve this situation, the JPEG Committee is developing a new coding standard called JPEG XT that is backward compatible to the popular JPEG compression, allowing it to be implemented using standard 8-bit JPEG coding hardware or software. In this paper, we present design principles and technical details of JPEG XT. It is based on a two-layer design, a base layer containing a low-dynamic-range image accessible to legacy implementations, and an extension layer providing the full dynamic range. The paper introduces three of currently defined profiles in JPEG XT, each constraining the common decoder architecture to a subset of allowable configurations. We assess the coding efficiency of each profile extensively through subjective assessments, using 24 naive subjects to evaluate 20 images, and objective evaluations, using 106 images with five different tone-mapping operators and at 100 different bit rates. The objective results (based on benchmarking with subjective scores) demonstrate that JPEG XT can encode HDR images at bit rates varying from 1.1 to 1.9 bit/pixel for estimated mean opinion score (MOS) values above 4.5 out of 5, which is considered as fully transparent in many applications. This corresponds to 23-times bitstream reduction compared to lossless OpenEXR PIZ compression.

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Overview and evaluation of the JPEG XT HDR image compression standard

Advances in computer graphics enable us to create digital images of astonishing complexity and realism. However, processing resources are still a limiting factor. Hence, many costly but desirable aspects of realism are often not accounted for, including global illumination, accurate depth of field and motion blur, spectral effects, etc. especially in real-time rendering. At the same time, there is a strong trend towards more pixels per display due to larger displays, higher pixel densities or larger fields of view. Further observable trends in current display technology include more bits per pixel high dynamic range, wider color gamut/fidelity, increasing refresh rates better motion depiction, and an increasing number of displayed views per pixel stereo, multi-view, all the way to holographic or lightfield displays. These developments cause significant unsolved technical challenges due to aspects such as limited compute power and bandwidth. Fortunately, the human visual system has certain limitations, which mean that providing the highest possible visual quality is not always necessary. In this report, we present the key research and models that exploit the limitations of perception to tackle visual quality and workload alike. Moreover, we present the open problems and promising future research targeting the question of how we can minimize the effort to compute and display only the necessary pixels while still offering a user full visual experience.

Perception-driven Accelerated Rendering

Given its potential for more realistic rendering and enhanced user experience, High Dynamic Range (HDR) imaging is raising a lot of interest both in industry and academia. In this context, efficient representation and coding techniques are needed, as HDR video entails significantly higher raw data rate. In this paper, we present a temporally constrained content-adaptive Tone Mapping Operator (TMO) in order to convert the input HDR video into a reduced bit depth video sequence which is then encoded using High Efficiency Video Coding (HEVC). As the proposed TMO simultaneously takes into account the statistical characteristics of the input frame while better preserving temporal coherence of the tone mapped video sequence, it leads to improved coding efficiency. Experimental results show that the proposed technique compares favorably with existing methods in terms of rate-distortion when using the HDR-VDP-2.2.1 quality metric.

HDR Video Coding based on a temporally constrained Tone Mapping Operator

In this paper, we address the problem of efficient High Dynamic Range (HDR) video coding. For this purpose, we introduce a new representation which segments the HDR image into low-range and highrange regions which are independently tone mapped. This representation allows preserving more information, leading to a higher visual quality of the reconstructed HDR image.

https://hal.archives-ouvertes.fr/hal-00973500/document

Paul Lauga

Papers

HDR Video Coding based on a temporally constrained Tone Mapping Operator

Region-based tone mapping for efficient High Dynamic Range video coding