[1]DU Weiwei.Colorization by classifying the prior knowledge[J].智能系统学报,2011,6(6):556560.
DU Weiwei.Colorization by classifying the prior knowledge[J].CAAI Transactions on Intelligent Systems,2011,6(6):556560.
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《智能系统学报》[ISSN 16734785/CN 231538/TP] 卷:
6
期数:
2011年第6期
页码:
556560
栏目:
学术论文—人工智能基础
出版日期:
20111225
 Title:

Colorization by classifying the prior knowledge
 文章编号:

16734785(2011)06055605
 作者:

DU Weiwei

Department of Information Science, Kyoto Institute of Technology, Kyoto, Japan 6068585
 Author(s):

DU Weiwei

Department of Information Science, Kyoto Institute of Technology, Kyoto, Japan 6068585

 关键词:

colorization; prior knowledge
 Keywords:

colorization; prior knowledge
 分类号:

TP18
 文献标志码:

A
 摘要:

When a onedimensional luminance scalar is replaced by a vector of a colorful multidimension for every pixel of a monochrome image, the process is called colorization. However, colorization is underconstrained. Therefore, the prior knowledge is considered and given to the monochrome image. Colorization using optimization algorithm is an effective algorithm for the above problem. However, it cannot effectively do with some images well without repeating experiments for confirming the place of scribbles. In this paper, a colorization algorithm is proposed, which can automatically generate the prior knowledge. The idea is that firstly, the prior knowledge crystallizes into some points of the prior knowledge which is automatically extracted by downsampling and upsampling method. And then some points of the prior knowledge are classified and given with corresponding colors. Lastly, the color image can be obtained by the color points of the prior knowledge. It is demonstrated that the proposal can not only effectively generate the prior knowledge but also colorize the monochrome image according to requirements of user with some experiments.
 Abstract:

When a onedimensional luminance scalar is replaced by a vector of a colorful multidimension for every pixel of a monochrome image, the process is called colorization. However, colorization is underconstrained. Therefore, the prior knowledge is considered and given to the monochrome image. Colorization using optimization algorithm is an effective algorithm for the above problem. However, it cannot effectively do with some images well without repeating experiments for confirming the place of scribbles. In this paper, a colorization algorithm is proposed, which can automatically generate the prior knowledge. The idea is that firstly, the prior knowledge crystallizes into some points of the prior knowledge which is automatically extracted by downsampling and upsampling method. And then some points of the prior knowledge are classified and given with corresponding colors. Lastly, the color image can be obtained by the color points of the prior knowledge. It is demonstrated that the proposal can not only effectively generate the prior knowledge but also colorize the monochrome image according to requirements of user with some experiments.
备注/Memo
Received Data： 20110815.
Corresponding Author： DU Weiwei. Email:duweiwei@dit.ac.jp.
About the authors：
DU Weiwei was born in 1978. She received PhD degree from Kyushu University in 2008, and now she is an asstistant professor at Kyoto Institute of Technology. Her current interests include fuzzy clusters and graphspectral algorithms, and she has authored or co authored several technical articles in journals and conference proceedings.
更新日期/Last Update:
20120229