On improving the pooling in HDR-VDP-2 towards better HDR perceptual quality assessment
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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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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.
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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 ArticleDOI
HDR-VDP-2: a calibrated visual metric for visibility and quality predictions in all luminance conditions
TL;DR: The visibility metric is shown to provide much improved predictions as compared to the original HDR-VDP and VDP metrics, especially for low luminance conditions, and is comparable to or better than for the MS-SSIM, which is considered one of the most successful quality metrics.
Proceedings ArticleDOI
A tone mapping algorithm for high contrast images
TL;DR: This work takes as an input a high dynamic range image and maps it into a limited range of luminance values reproducible by a display device and follows functionality of HVS without attempting to construct its sophisticated model.
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iCAM06: A refined image appearance model for HDR image rendering
TL;DR: Evaluation of the model proved iCAM06 to have consistently good HDR rendering performance in both preference and accuracy making it a good candidate for a general-purpose tone-mapping operator with further potential applications to a wide-range of image appearance research and practice.
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Advanced High Dynamic Range Imaging: Theory and Practice
TL;DR: This book provides a practical introduction to the emerging new discipline of high dynamic range imaging that combines photography and computer graphics by providing detailed equations and code that gives the reader the tools needed to experiment with new techniques for creating compelling images.
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Backward compatible high dynamic range MPEG video compression
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