AN IMAGE COLORIZATION ALGORITHM USING SPARSE OPTIMIZATION

被引：0

作者：

Uruma, Kazunori ^{[1
]}

Konishi, Katsumi ^{[2
]}

Takahashi, Tomohiro ^{[1
]}

Furukawa, Toshihiro ^{[1
]}

机构：

[1] Tokyo Univ Sci, Grad Sch Engn, Tokyo 162, Japan

[2] Kogakuin Univ, Dept Comp Sci, Tokyo 160, Japan

来源：

2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2013年

关键词：

image colorization; sparse optimization; IRLS algorithm;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

This paper proposes a new digital image colorization algorithm using the sparse optimization. We deal with the colorization problem where a grayscale image is colorized using a full color image with a similar composition, and formulate this problem as the sparse optimization problem. We also provide an iterative reweighted least squares (IRLS) algorithm to solve this problem approximately, and the full color image is obtained in practical time. Numerical examples show that the proposed algorithm colorizes a grayscale image well.

引用

页码：1588 / 1592

页数：5

共 8 条

[1] Enhancing Sparsity by Reweighted l1 Minimization [J].