Fully-automatic inverse tone mapping algorithm based on dynamic mid-level tone mapping
Gonzalo Luzardo,Jan Aelterman,Hiep Luong,Sven Rousseaux,Daniel Ochoa,Wilfried Philips +5 more
- Vol. 9, Iss: 1
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TLDR
Experimental results demonstrate that the proposed fully-automatic inverse tone mapping operator based on mid-level mapping capable of real-time video processing outperforms the current state-of-the-art of simple inversetone mapping methods and its performance is similar to other more complex and time-consuming advanced techniques.Abstract:
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.read more
Citations
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A Fully Automatic Content Adaptive Inverse Tone Mapping Operator With Improved Color Accuracy
TL;DR: This paper proposes a novel content adaptive iTMO that works in the perceptual domain to model the sensitivity of the human eye to brightness changes in different areas of a scene and outperforms other state-of-the-art methods in terms of visual quality and color adjustment.
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Highlights Analysis System (HAnS) for Low Dynamic Range to High Dynamic Range Conversion of Cinematic Low Dynamic Range Content
TL;DR: The experimental analysis shows that the proposed approach outperforms conventional highlights detection algorithms on both image data-sets, achieves high quality reconstruction of the HDR content and is suited for use in LDR-to-HDR conversion.
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Perception-based high dynamic range video compression with optimal bit-depth transformation
TL;DR: An HDR compression method based on an optimized bit-depth transformation, and HVS model based wavelet transform denoising is proposed, which outperforms previous approaches and operates in accordance with characteristics of the HVS.
Journal ArticleDOI
Differential Evolution-based Approach for Tone-Mapping of High Dynamic Range Images
TL;DR: The optimization process is based on the differential evolution (DE) algorithm which takes tone-mapping function of an existing histogram-based method as initial guess and refines the histogram bins iteratively leading to progressive enhancement of the quality of LDR image.
Journal ArticleDOI
Learning a Practical SDR-to-HDRTV Up-conversion using New Dataset and Degradation Models
TL;DR: Guo et al. as discussed by the authors proposed a luminance-segmented network (LSN) consisting of a global mapping trunk, and two Transformer branches on bright and dark luminance range.
References
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