Mr. Jionghui Song Profile

Jionghui Song

at Zhejiang Univ

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Proceedings Article | 5 November 2020 Paper

Dual-focal camera HDR imaging based on convolutional neural network

Jionghui Song, Qi Li, Huajun Feng, Zhihai Xu, Yueting Chen

Proceedings Volume 11567, 115673L (2020) https://doi.org/10.1117/12.2580208

KEYWORDS: High dynamic range imaging, Cameras, Image fusion, Imaging systems, Image registration, Image processing, Convolutional neural networks, Image resolution, Spatial resolution

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In this paper, we propose a method which is based on the dual-focal camera facing the same target to expanse the dynamic range of images. Since the spatial resolution of dual-focal camera in this paper is different, down-sampling, up-sampling, and multi-resolution fusion are required in image fusion processing to obtain an ideal high dynamic range image. The current multi-frame high dynamic range algorithm is mainly for similar resolution images. When there are two images with large resolution differences, The effect of ordinary registration algorithms (For example, optical flow registration algorithm) are limited, and the image may appear ghost and color artifacts after registration. Our method uses a convolutional neural network, which composed of two subnets. An image fusion subnet and a style transfer subnet. Because there is only one exposure image in the surrounding field of view, the central field of view is processed separately from the surrounding field of view. In the central field of view, U-Net is used to register the images layer by layer to increase the registration speed and registration accuracy. After the high dynamic range image in the central field of view, the style transfer network is used to transfer the color distribution of the high dynamic range image to the surrounding field of view. As for result, we performed extensive qualitative and quantitative comparisons to show that our method produces excellent results where ghost and color artifacts are significantly reduced compared to existing general multi-frame high dynamic range methods, and is robust across various inputs.

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