针对高动态范围(high dynamic range, HDR)图像较为复杂耗时的合成流程, 提出一种基于生成对抗网络的 HDR 图像风格迁移技术. 首先, 构建两个生成对抗网络的训练集: 普通图片与低曝光 HDR 图片, 普通图片与高曝光 HDR 图片; 然后, 通过生成对抗网络训练, 得到普通图片到低曝光 HDR 图片和普通图片到高曝光 HDR 图片两个生成模型; 最后, 将模型输出的高低曝光图像和原图合成 HDR 文件, 再通过色调映射形成最终 HDR 风格迁移后的图像. 实验结果表明, 这种方法不仅有效解决了 HDR 图像风格迁移问题, 也充分表明了生成对抗网络在图像编辑中的优越性.

In view of the complex and time-consuming synthetic process of the high dynamic range (HDR) images, a novel HDR image transfer technique based on the generative adversarial network has been proposed. The process is as follows: first to build two training sets of the generative adversarial network---ordinary images and low-exposure HDR images; ordinary images and high exposure HDR images. Then, through the training of the generative adversarial networks, the two generative models of ordinary images to low exposure HDR images and ordinary images to high exposure HDR images are established. Finally, a picture is put into the model, the high and low exposure images and the original images are combined to synthesize HDR files, and the tone mapping forms the image after the final HDR style transfer. This method not only solves effectively the problem of HDR image style transfer, but also proves the advantages of the generative adversarial network in processing image editing.