Invertible Grayscale
文献类型:期刊论文
作者 | MENGHAN XIA; XUETING LIU; TIEN-TSIN WONG |
刊名 | ACM Transactions on Graphics
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出版日期 | 2018 |
文献子类 | 期刊论文 |
英文摘要 | Once a color image is converted to grayscale, it is a common belief that the original color cannot be fully restored, even with the state-of-the-art colorization methods. In this paper, we propose an innovative method to synthesize invertible grayscale. It is a grayscale image that can fully restore its original color. The key idea here is to encode the original color information into the synthesized grayscale, in a way that users cannot recognize any anomalies.We propose to learn and embed the color-encoding scheme via a convolutional neural network (CNN). It consists of an encoding network to convert a color image to grayscale, and a decoding network to invert the grayscale to color. We then design a loss function to ensure the trained network possesses three required properties: (a) color invertibility, (b) grayscale conformity, and (c) resistance to quantization error. We have conducted intensive quantitative experiments and user studies over a large amount of color images to validate the proposed method. Regardless of the genre and content of the color input, convincing results are obtained in all cases. |
语种 | 英语 |
源URL | [http://ir.siat.ac.cn:8080/handle/172644/13560] ![]() |
专题 | 深圳先进技术研究院_集成所 |
推荐引用方式 GB/T 7714 | MENGHAN XIA,XUETING LIU,TIEN-TSIN WONG. Invertible Grayscale[J]. ACM Transactions on Graphics,2018. |
APA | MENGHAN XIA,XUETING LIU,&TIEN-TSIN WONG.(2018).Invertible Grayscale.ACM Transactions on Graphics. |
MLA | MENGHAN XIA,et al."Invertible Grayscale".ACM Transactions on Graphics (2018). |
入库方式: OAI收割
来源:深圳先进技术研究院
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