| Color to Gray: Visual Cue Preservation | |
| Song, Mingli1; Tao, Dacheng2; Chen, Chun1; Li, Xuelong3; Chen, Chang Wen4; M. Song | |
| 2010-09-01 | |
| 发表期刊 | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
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| ISSN | 0162-8828 |
| 卷号 | 32期号:9页码:1537-1552 |
| 摘要 | Both commercial and scientific applications often need to transform color images into gray-scale images, e. g., to reduce the publication cost in printing color images or to help color blind people see visual cues of color images. However, conventional color to gray algorithms are not ready for practical applications because they encounter the following problems: 1) Visual cues are not well defined so it is unclear how to preserve important cues in the transformed gray-scale images; 2) some algorithms have extremely high time cost for computation; and 3) some require human-computer interactions to have a reasonable transformation. To solve or at least reduce these problems, we propose a new algorithm based on a probabilistic graphical model with the assumption that the image is defined over a Markov random field. Thus, color to gray procedure can be regarded as a labeling process to preserve the newly well-defined visual cues of a color image in the transformed gray-scale image. Visual cues are measurements that can be extracted from a color image by a perceiver. They indicate the state of some properties of the image that the perceiver is interested in perceiving. Different people may perceive different cues from the same color image and three cues are defined in this paper, namely, color spatial consistency, image structure information, and color channel perception priority. We cast color to gray as a visual cue preservation procedure based on a probabilistic graphical model and optimize the model based on an integral minimization problem. We apply the new algorithm to both natural color images and artificial pictures, and demonstrate that the proposed approach outperforms representative conventional algorithms in terms of effectiveness and efficiency. In addition, it requires no human-computer interactions. |
| 文章类型 | Article |
| 关键词 | Color To Gray Probabilistic Graphical Model Visual Cue |
| 学科领域 | 信号与模式识别 |
| WOS标题词 | Science & Technology ; Technology |
| DOI | 10.1109/TPAMI.2009.74 |
| 收录类别 | SCI ; EI |
| 关键词[WOS] | IMAGES ; CONVERSION ; TEXTURE |
| 语种 | 英语 |
| WOS研究方向 | Computer Science ; Engineering |
| WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
| WOS记录号 | WOS:000279969000001 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.opt.ac.cn/handle/181661/8560 |
| 专题 | 光谱成像技术研究室 |
| 通讯作者 | M. Song |
| 作者单位 | 1.Zhejiang Univ, Coll Comp Sci, Hangzhou 310027, Zhejiang, Peoples R China 2.Nanyang Technol Univ, Sch Comp Engn, Singapore 639798, Singapore 3.Chinese Acad Sci, State Key Lab Transient Opt & Photon, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China 4.SUNY Buffalo, Dept Comp Sci & Engn, Buffalo, NY 14260 USA |
| 推荐引用方式 GB/T 7714 | Song, Mingli,Tao, Dacheng,Chen, Chun,et al. Color to Gray: Visual Cue Preservation[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2010,32(9):1537-1552. |
| APA | Song, Mingli,Tao, Dacheng,Chen, Chun,Li, Xuelong,Chen, Chang Wen,&M. Song.(2010).Color to Gray: Visual Cue Preservation.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,32(9),1537-1552. |
| MLA | Song, Mingli,et al."Color to Gray: Visual Cue Preservation".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 32.9(2010):1537-1552. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Color to Gray: Visua（3827KB） | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 请求全文 | |
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