| Citation: | BEI Yue, WANG Qi, CHENG Zhipeng, et al. HDR image generation method based on conditional generative adversarial network[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(1): 45-52. doi: 10.13700/j.bh.1001-5965.2020.0518(in Chinese)
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Compared with low dynamic range (LDR) images, high dynamic range (HDR) images have a wider color gamut and higher brightness range, which is more in line with human visual effects. However, since most of the current image acquisition devices are LDR devices, HDR image resources are scarce. An effective way to solve this problem is to map LDR images to HDR images through inverse tone mapping. This paper proposes an inverse tone mapping algorithm based on conditional generative adversarial network (CGAN) to reconstruct HDR images. To this end, a multi-branch-based generation network and a discrimination network based on discrimination blocks are designed, and the data generation and feature extraction capabilities of CGAN are used to map a single LDR image from the BT.709 color gamut to the corresponding BT.2020 color area. The experimental results show that the proposed network can obtain higher objective and subjective quality compared with the existing methods. Especially for fuzzy areas in the low color gamut, the proposed method can reconstruct clearer textures and details.
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