A review for Tone-mapping Operators on Wide Dynamic Range Image
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Abstract (arXiv)
The dynamic range of our normal life can exceeds 120 dB, however, the smart-phone cameras and the conventional digital cameras can only capture a dynamic range of 90 dB, which sometimes leads to loss of details for the recorded image. Now, some professional hardware applications and image fusion algorithms have been devised to take wide dynamic range (WDR), but unfortunately existing devices cannot display WDR image. Tone mapping (TM) thus becomes an essential step for exhibiting WDR image on our ordinary screens, which convert the WDR image into low dynamic range (LDR) image. More and more researchers are focusing on this topic, and give their efforts to design an excellent tone mapping operator (TMO), showing detailed images as the same as the perception that human eyes could receive. Therefore, it is important for us to know the history, development, and trend of TM before proposing a practicable TMO. In this paper, we present a comprehensive study of the most well-known TMOs, which divides TMOs into traditional and machine learning-based category.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 8 of its 27 references that are in the map. First posted on arXiv 8 Jan 2021.
Builds on
8 of 27 references.
References · 8
- 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
- 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
- 2016V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentationcited by 2,284
- 2016Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Networkcited by 1,898
- 2017Deep High Dynamic Range Imaging with Large Foreground Motionscited by 98
- 2015Convolutional Neural Network Architectures for Matching Natural Language Sentencescited by 82
- 2019Deep Tone Mapping Operator for High Dynamic Range Imagescited by 26
- 2020Explorable Tone Mapping Operatorscited by 6
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Citing papers per year: 2023: 1.
1 paper.