A NR-IQA based deep neural network for tone mapping HDR images

Minseok Choi; Pilkyu Park; Kwang Pyo Choi; Tejas Nair

doi:10.1117/12.2528617

6 September 2019 A NR-IQA based deep neural network for tone mapping HDR images

Minseok Choi, Pilkyu Park, Kwang Pyo Choi, Tejas Nair

Proceedings Volume 11137, Applications of Digital Image Processing XLII; 111370S (2019) https://doi.org/10.1117/12.2528617
Event: SPIE Optical Engineering + Applications, 2019, San Diego, California, United States

Abstract

The most recent High Dynamic Range (HDR) standard, HDR10+, achieves good picture quality by incorporating dynamic metadata that carry frame-by-frame information for tone mapping while most HDR standards use static tone mapping curves that apply across the entire video. Since it is laborious to acquire hand-crafted best-fitting tone mapping curve for each frame, there have been attempts to derive the curves from input images. This paper proposes the neural network framework that generates tone mapping on a frame-by-frame basis. Although a number of successful tone mapping operators (TMOs) have been proposed over the years, evaluation of tone mapped images still remains a challenging topic. We define an objective measure to evaluate tone mapping based on Non-Reference Image Quality Assessment (NR-IQA). Experiments show that the framework produces good tone mapping curves and makes the video more vivid and colorful.

Conference Presentation

Citation Download Citation

Minseok Choi, Pilkyu Park, Kwang Pyo Choi, and Tejas Nair "A NR-IQA based deep neural network for tone mapping HDR images", Proc. SPIE 11137, Applications of Digital Image Processing XLII, 111370S (6 September 2019); https://doi.org/10.1117/12.2528617

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