Remote Sensing Image Colorization Based on Multiscale SEnet GAN

Min Wu, Xin Jin, Qian Jiang, Shin Jye Lee, Lin Guo, Yide Di, Shanshan Huang, Jinfang Huang

研究成果: Conference contribution同行評審

1 引文 斯高帕斯(Scopus)

摘要

Image colorization technique is to colorize the grayscale images or single-channel images. In the research of image colorization, the coloring of remote sensing images is a challenging problem. This paper proposes a new method of remote sensing image colorization method based on Deep Convolution Generative Adversarial Network (DCGAN). We combine multi-scale convolution with Squeeze-and-Excitation Networks (SEnet) to propose a new model that is applied to the generator of DCGAN. Therefore, the generator not only retains the largest image features in the process of the generating images, but also can adjust the channel weights in the training process. We have compared the proposed method with other image colorization methods, and the results show that the proposed method has a good performance on both human vision and image evaluation indicators on the colorization of remote sensing images.

原文English
主出版物標題Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019
編輯Qingli Li, Lipo Wang
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781728148526
DOIs
出版狀態Published - 十月 2019
事件12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019 - Huaqiao, China
持續時間: 19 十月 201921 十月 2019

出版系列

名字Proceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019

Conference

Conference12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019
國家China
城市Huaqiao
期間19/10/1921/10/19

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