Fifty shades of HDR

Chalmers, Alan; Karr, Brian A.; Suma, R.; Debattista, Kurt

doi:10.1109/dmiaf.2016.7574902

Cited by 5 publications

(5 citation statements)

References 33 publications

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“…Perceptual encoding can exploit knowledge of the HVS, such as the fact the HVS is able to discern luminance threshold differences more clearly in darker areas than brighter ones to achieve efficient encoding [57]. However, for computer vision applications, such perceptual encoding may result in detail in the scene being missed or over-accentuated by the computer vision algorithms [44,58,59]. Simple linear encoding is not the answer either.…”

Section: Linear Vs Perceptual Encodingmentioning

confidence: 99%

HDR video past, present and future: A perspective

Chalmers

Debattista

2017

Signal Processing: Image Communication

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High Dynamic Range (HDR) video has emerged from research labs around the world and entered the realm of consumer electronics. The dynamic range that a human can see in a scene with minimal eye adaption (approximately 1,000,000 : 1) is vastly greater than traditional imaging technology which can only capture about 8 f-stops (256 : 1). HDR technology, on the other hand, has the potential to capture the full range of light in a scene; even more than a human eye can see. This paper examines the field of HDR video from capture to display; past, present and future. In particular the paper looks beyond the current marketing hype around HDR, to show how HDR video in the future can and, indeed, should bring about a step change in imaging, analogous to the change from black and white to colour.

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Section: Linear Vs Perceptual Encodingmentioning

confidence: 99%

HDR video past, present and future: A perspective

Chalmers

Debattista

2017

Signal Processing: Image Communication

Self Cite

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“…HDR imaging overcomes the dynamic range limitations of traditional LDR imaging by capturing the full range of the visible light spectrum and colors that exist in the real world by performing operations at high bit-depths [2]. Hence, HDR technology is capable of enhancing the quality of television experience with a dynamic range compared to the Human Visual System (HVS) [3].…”

Section: Introductionmentioning

confidence: 99%

“…Different techniques have been proposed in the past few years, each of them addresses the problem of inverse tone mapping in a different way. Common limitations of these techniques are (1) they need human intervention to decide the most suitable parameters to use for the inverse tone mapping, (2) they are limited to produce HDR images with a limited peak brightness (between 1000 and 3000 nits), (3) they are designed to preserve the appearance of the original LDR image without considering the artistic intentions inherent to the HDR domain (like deep shadows and bright highlights), and (4) they are complex and their computation times are so high that they are not suitable for practical purposes such as real-time inverse tone mapping or being embedded on hardware with limited resources.…”

Section: Introductionmentioning

confidence: 99%

“…Considering that the human eye can see 14 stops of dynamic range in a single view; clearly, conventional display technology is unable to show luminance-realistic images. 1 imec-IPI-UGent, Ghent University, Sint-Pietersnieuwstraat 41, 9000 Ghent, Belgium 2 Facultad de Ingeniería en Electricidad y Computación, ESPOL Polytechnic University, Campus Gustavo Galindo Km. 30.5 Vía Perimetral, Guayaquil, Ecuador 3 Vlaamse Radio -en Televisieomroeporganisatie, Auguste Reyerslaan 52, Brussels, Belgium Images associated to display technology with narrow dynamic range and a low brightness have been retroactively called Low Dynamic Range (LDR) images.…”

Section: Introductionmentioning

confidence: 99%

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Fully-automatic inverse tone mapping algorithm based on dynamic mid-level tone mapping

Luzardo

Aelterman

Luong

et al. 2020

SIP

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High Dynamic Range (HDR) displays can show images with higher color contrast levels and peak luminosities than the common Low Dynamic Range (LDR) displays. However, most existing video content is recorded and/or graded in LDR format. To show LDR content on HDR displays, it needs to be up-scaled using a so-called inverse tone mapping algorithm. Several techniques for inverse tone mapping have been proposed in the last years, going from simple approaches based on global and local operators to more advanced algorithms such as neural networks. Some of the drawbacks of existing techniques for inverse tone mapping are the need for human intervention, the high computation time for more advanced algorithms, limited low peak brightness, and the lack of the preservation of the artistic intentions. In this paper, we propose a fully-automatic inverse tone mapping operator based on mid-level mapping capable of real-time video processing. Our proposed algorithm allows expanding LDR images into HDR images with peak brightness over 1000 nits, preserving the artistic intentions inherent to the HDR domain. We assessed our results using the full-reference objective quality metrics HDR-VDP-2.2 and DRIM, and carrying out a subjective pair-wise comparison experiment. We compared our results with those obtained with the most recent methods found in the literature. Experimental results demonstrate that our proposed method outperforms the current state-of-the-art of simple inverse tone mapping methods and its performance is similar to other more complex and time-consuming advanced techniques.

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“…Keywords High Dynamic Range • Inverse Tone Mapping • Subjective study 1 Introduction High Dynamic Range (HDR) is considered an important next step in the evolution of television technology. HDR imaging overcomes the dynamic range limitations of traditional imaging by capturing the full range of the visible light spectrum (e.g., highlights and deeper tones) and colors that exist in the real world by performing operations at high bit-depths [7]. Dynamic range refers to the ratio between the brightest whites and darkest blacks present in an image, and it is commonly measured in f-stops (or simply stops), which is the logarithm of the ratio.…”

mentioning

confidence: 99%

An experimental study on the perceived quality of natively graded versus inverse tone mapped high dynamic range video content on television

Luzardo

Vyvey

Aelterman

et al. 2020

Multimed Tools Appl

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High Dynamic Range (HDR) television promises to display higher brightness and deeper black levels and thus more vivid and realistic images. However, home video distribution and video broadcasting were historically designed for what we now call standard dynamic range screens (SDR). In order to display SDR content on an HDR screen, it is explicitly or implicitly converted, in a process called inverse tone mapping (iTMO). This paper's goal is to assess the perceived quality of converted SDR content in comparison to natively graded HDR content. In doing so, this paper aims to enable content creators/distributors to make informed choices between creating/broadcasting HDR content or relying on conversion. To this end, a psychophysical experiment was performed to tests how viewers evaluate the difference between natively graded HDR and a set of SDR

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Fifty shades of HDR

Cited by 5 publications

References 33 publications

HDR video past, present and future: A perspective

HDR video past, present and future: A perspective

Fully-automatic inverse tone mapping algorithm based on dynamic mid-level tone mapping

An experimental study on the perceived quality of natively graded versus inverse tone mapped high dynamic range video content on television

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