Adversarial and Adaptive Tone Mapping Operator for High Dynamic Range Images

Author:

Cao X.,Lai K.,Yanushkevich S.N.,Smith M. R.

Funder

Natural Sciences and Engineering Research Council of Canada

Biomet

Mitacs

Publisher

IEEE

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. X-ray image enhancement with multi-scale local edge preserving filter based on fuzzy entropy;Journal of X-Ray Science and Technology;2024-08-16

2. Improving HDR Rendering with UMTMNet’s Multilayer Perception;2023 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics);2023-12-17

3. Hardware-friendly tone-mapping operator design and implementation for real-time embedded vision applications;Computers and Electrical Engineering;2023-09

4. High Dynamic Range Image Tone Mapping: Literature review and performance benchmark;Digital Signal Processing;2023-06

5. A Generative Adversarial Network Based Tone Mapping Operator for 4K HDR Images;2023 International Conference on Computing, Networking and Communications (ICNC);2023-02-20

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