A fast colorization method of grayscale image based on neural network

Qiang Zhang; Wei Li

doi:10.1117/12.2637065

15 June 2022 A fast colorization method of grayscale image based on neural network

Qiang Zhang, Wei Li

Proceedings Volume 12285, International Conference on Advanced Algorithms and Neural Networks (AANN 2022); 122850B (2022) https://doi.org/10.1117/12.2637065
Event: International Conference on Advanced Algorithms and Neural Networks (AANN 2022), 2022, Zhuhai, China

Abstract

Using deep learning to colorize grayscale images often requires the preparation of a large number of training images, which also requires very high computing power. In view of this situation, this paper designs a fast colorization method for grayscale images that combines traditional feature extraction with a simple neural network. The method is mainly divided into three steps: Firstly, select the reference color image and train the network, then the target gray image is input into the network to generate the first stage color image; Next, the color image obtained in the previous step is transformed into HSV space, only the V component is retained, and the gray value of the target gray image is used for color synthesis to obtain the second stage color image with clear texture; Finally, the Reinhard algorithm is used for color migration, and then the reference color image is used to color the target image accurately to obtain the third stage color image. Experiments demonstrated that the algorithm proposed is fast, efficient, and robust.

Citation Download Citation

Qiang Zhang and Wei Li "A fast colorization method of grayscale image based on neural network", Proc. SPIE 12285, International Conference on Advanced Algorithms and Neural Networks (AANN 2022), 122850B (15 June 2022); https://doi.org/10.1117/12.2637065

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