HDR and wide gamut appearance-based color encoding and its quantification

Kunkel, Timo; Ward, Greg; Lee, Bongsun; Daly, Scott

doi:10.1109/pcs.2013.6737757

Cited by 11 publications

(6 citation statements)

References 10 publications

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“…However, as mentioned in Section 2, an image signal is quantized in a perceptually encoded domain in order to optimize the bit-depth usage with respect to the HVS. In HDR, the most common linear to perceptual domain transformation used is the SMPTE ST 2084 standard transfer function [6], also known as Perceptual Quantizer (PQ) [7]. Distributed HDR signal is mostly quantized in either 10 or 12 bits while PQ has been reported to require no more than 11 bits to represent gray patches without any visual loss [8] (natural images are reported to require no more than 10 bits [9]).…”

Section: Displaying High Dynamic Range Signalmentioning

confidence: 99%

42‐1: Invited Paper: Bit‐Depth Constrained Black Level for High Dynamic Range Displays

Boitard¹,

Ploumis

Damberg³

et al. 2019

Symp Digest of Tech Papers

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High Dynamic Range (HDR) workflows provide increased peak luminance and lower black levels leading to a significantly enhanced quality of experience. HDR pixels also represent more tonal values across the dynamic range by using a higher bitdepth along with different perceptual transfer functions. However, many light emitting display devices modulate light using a limited bit-depth in the linear domain. It is thus challenging for such display systems to achieve simultaneously high peak luminance and high amount of information in the shadows. In this paper, we assess the required bit-depth to accurately reproduce the shadow information of an HDR signal for different display capabilities.

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Section: Displaying High Dynamic Range Signalmentioning

confidence: 99%

42‐1: Invited Paper: Bit‐Depth Constrained Black Level for High Dynamic Range Displays

Boitard¹,

Ploumis

Damberg³

et al. 2019

Symp Digest of Tech Papers

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“…spatial analysis (Saliency maps, Fourier analyses, VDP/HDR-VDP [6]), temporal analysis (Frame rate behavior, Judder [7], etc.) and colorimetric analysis (color volume calculation [8], Impact of Display Management based on theoretical source and target display parameters) are the general tools used to accomplish this. The measurement set-up approach uses actual metrological methods to assess the performance of the actual display either with test patterns or with real content.…”

Section: -1 / T Kunkel Invited Papermentioning

confidence: 99%

65-1:Invited Paper: Characterizing High Dynamic Range Display System Properties in the Context of Today's Flexible Ecosystems

Kunkel

Spears²,

Atkins

et al. 2016

SID Symposium Digest of Technical Papers

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The transition from standard dynamic range (SDR) imaging systems whose characteristics were largely derived from the capabilities of CRT displays is well underway toward a newer ecosystem with higher capabilities. The newer ecosystem improves color volume aspects such as high dynamic range (HDR) and wide color gamut (WCG), as well as improvements in other dimensions such as bit-depth, spatial resolution, energy, thermal management, field-of-view, mobility, and frame rate. More importantly, since there will not be one single predominating display technology, a large variability of color volumes will result. Thus, the newer ecosystem needs to tailor the imagery to the specific display. Achieving such an ecosystem that includes flexible delivery methods such as the internet, broadcast, and solid-state memory-based storage media, displays must be characterized much more completely than they have for previous broadcast and disc-based storage media ecosystems standards. This paper focuses on the color volume aspects (HDR, WCG) of such needed characterization, as well as key spatial aspects that relate to modern single and dual modulation display technology and power saving.

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“…This model allows to regain some sort of control on tone mapped content, but it is less optimal in term of compression eciency. That is why, the new trend in HDR video compression is based on a perceptual curve, also called inverse Electro-Optic Transfer Function(EOT F −1 ), that transforms HDR sequence (oating-point data) into a high bit-depth representation (integer data with quantization step not visible by the human eye) [Mantiuk et al, 2004, Mantiuk et al, 2006b, Motra and Thoma, 2010, Miller et al, 2013, Kunkel et al, 2013. The generated video is directly compressed using a single high-bit depth codec.…”

Section: Hevcmentioning

confidence: 99%

“…Two main transforms are of interest for video compression: the Electro-Optic Transfer Function (EOTF) and the color dierence encoding. EOTF is a constant transformation that encodes luminance values to luma values [Mantiuk et al, 2004, Miller et al, 2013, Kunkel et al, 2013, Touzé et al, 2014.…”

Section: Hdr Color Encodingmentioning

confidence: 99%

Temporal coherency for video tone mapping

et al. 2012

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International audienceTone Mapping Operators (TMOs) aim at converting real world high dynamic range (HDR) images captured withHDR cameras, into low dynamic range (LDR) images that can be displayed on LDR displays. Several TMOshave been proposed over the last decade, from the simple global mapping to the more complex one simulating thehuman vision system. While these solutions work generally well for still pictures, they are usually less efficient forvideo sequences as they are source of visual artifacts. Only few of them can be adapted to cope with a sequenceof images. In this paper we present a major problem that a static TMO usually encounters while dealing withvideo sequences, namely the temporal coherency. Indeed, as each tone mapper deals with each frame separately,no temporal coherency is taken into account and hence the results can be quite disturbing for high varyingdynamics in a video. We propose a temporal coherency algorithm that is designed to analyze a video as a whole,and from its characteristics adapts each tone mapped frame of a sequence in order to preserve the temporalcoherency. This temporal coherency algorithm has been tested on a set of real as well as Computer GraphicsImage (CGI) content and put in competition with several algorithms that are designed to be time-dependent.Results show that temporal coherency preserves the overall contrast in a sequence of images. Furthermore, thistechnique is applicable to any TMO as it is a post-processing that only depends on the used TMO

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HDR and wide gamut appearance-based color encoding and its quantification

Cited by 11 publications

References 10 publications

42‐1: Invited Paper: Bit‐Depth Constrained Black Level for High Dynamic Range Displays

42‐1: Invited Paper: Bit‐Depth Constrained Black Level for High Dynamic Range Displays

65-1:Invited Paper: Characterizing High Dynamic Range Display System Properties in the Context of Today's Flexible Ecosystems

Temporal coherency for video tone mapping

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