Research on Image Colorization Algorithm Based on Residual Neural Network

Pinle Qin, Zirui Cheng, Yuhao Cui, Jinjing Zhang, Qiguang Miao

Abstract: In order to colorize the grayscale images efficiently, an image colorization method based on deep residual neural network is proposed. This method combines the classified information and features of the image, uses the whole image as the input of the network and forms a non-linear mapping from grayscale images to the colorful images through the deep network. The network is trained by using the MIT Places Database and ImageNet and colorizes the grayscale images. The experiment result shows that different data sets have different colorization effects on grayscale images, and the complexity of the network determines the colorization effect of grayscale images. This method can colorize the grayscale images efficiently, which has better visual effect.