On improving the pooling in HDR-VDP-2 towards better HDR perceptual quality assessment
TLDR
The HDR Visual Difference Predictor (HDR-VDP-2) is primarily a visibility prediction metric i.e. whether the signal distortion is visible to the eye and to what extent and it also employs a pooling function to compute an overall quality score.Abstract:
High Dynamic Range (HDR) signals capture much higher contrasts as compared to the traditional 8-bit low dynamic range (LDR) signals. This is achieved by representing the visual signal via values that are related to the real-world luminance, instead of gamma encoded pixel values which is the case with LDR. Therefore, HDR signals cover a larger luminance range and tend to have more visual appeal. However, due to the higher luminance conditions, the existing methods cannot be directly employed for objective quality assessment of HDR signals. For that reason, the HDR Visual Difference Predictor (HDR-VDP-2) has been proposed. HDR-VDP-2 is primarily a visibility prediction metric i.e. whether the signal distortion is visible to the eye and to what extent. Nevertheless, it also employs a pooling function to compute an overall quality score. This paper focuses on the pooling aspect in HDR-VDP-2 and employs a comprehensive database of HDR images (with their corresponding subjective ratings) to improve the prediction accuracy of HDR-VDP-2. We also discuss and evaluate the existing objective methods and provide a perspective towards better HDR quality assessment.read more
Citations
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Journal ArticleDOI
Hdr-vqm
TL;DR: An objective HDR video quality measure (HDR-VQM) based on signal pre-processing, transformation, and subsequent frequency based decomposition is presented, which is one of the first objective method for high dynamic range video quality estimation.
Journal ArticleDOI
Perception-driven Accelerated Rendering
Martin Weier,Martin Weier,Michael Stengel,Michael Stengel,Thorsten Roth,Thorsten Roth,Piotr Didyk,Elmar Eisemann,Martin Eisemann,Steve Grogorick,André Hinkenjann,Ernst Kruijff,Marcus Magnor,Karol Myszkowski,Philipp Slusallek,Philipp Slusallek,Philipp Slusallek +16 more
TL;DR: This report presents the key research and models that exploit the limitations of perception to tackle visual quality and workload alike, and presents the open problems and promising future research targeting the question of how to minimize the effort to compute and display only the necessary pixels while still offering a user full visual experience.
Proceedings ArticleDOI
Performance evaluation of objective quality metrics for HDR image compression
TL;DR: The performance of HDR-VDP is compared to that of PSNR and SSIM computed on perceptually encoded luminance values, when considering compressed HDR images, to show that these simpler metrics can be effectively employed to assess image fidelity for applications such as HDR image compression.
Journal ArticleDOI
No-reference image quality assessment based on hybrid model
TL;DR: A computational algorithm based on hybrid model to automatically extract vision perception features from raw image patches is proposed, which demonstrates very competitive quality prediction performance of the proposed method.
Proceedings ArticleDOI
Crowdsourcing evaluation of high dynamic range image compression
TL;DR: The crowdsourcing evaluations show that some TMOs are more suitable for evaluation of HDR image compression, compared to a reference ground truth obtained via a subjective assessment of the same HDR images on a Dolby `Pulsar' HDR monitor in a laboratory environment.
References
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Proceedings Article
JPEG-HDR: A Backwards-Compatible, High Dynamic Range Extension to JPEG.
Greg Ward,Maryann Simmons +1 more
TL;DR: This paper demonstrates a simple approach to HDR encoding that parallels the evolution of color television from its grayscale beginnings, and extends the color range to encompass the visible gamut, enabling a new generation of display devices that are just beginning to enter the market.
Proceedings ArticleDOI
JPEG-HDR: a backwards-compatible, high dynamic range extension to JPEG
Greg Ward,Maryann Simmons +1 more
TL;DR: In this paper, a tone-mapped version of each HDR original is accompanied by restorative information carried in a subband of a standard output-referred image, which when multiplied by the tonemapped foreground, recovers the HDR original.
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TL;DR: A new image quality assessment algorithm based on the phase and magnitude of the 2-D discrete Fourier transform that is overall better than several of the existing full-reference algorithms and two RR algorithms and further scalable for RR scenarios.
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