计算机应用 ›› 2016, Vol. 36 ›› Issue (4): 1075-1079.DOI: 10.11772/j.issn.1001-9081.2016.04.1075

• 虚拟现实与数字媒体 • 上一篇    下一篇

多传感器彩色纹理色彩差异修正方法

马倩1,2, 葛宝臻1,2, 陈雷1,2,3   

  1. 1. 天津大学 精密仪器与光电子工程学院, 天津 300072;
    2. 光电信息技术科学教育部重点实验室(天津大学), 天津 300072;
    3. 天津商业大学 信息工程学院, 天津 300134
  • 收稿日期:2015-09-01 修回日期:2015-10-25 出版日期:2016-04-10 发布日期:2016-04-08
  • 通讯作者: 陈雷
  • 作者简介:马倩(1990-),女,河北保定人,硕士研究生,主要研究方向:激光三维彩色数字成像; 葛宝臻(1964-),男,内蒙古卓资人,教授,博士,主要研究方向:激光三维彩色数字成像、光电检测、激光粒子测量; 陈雷(1980-),男,河北唐山人,副教授,博士,主要研究方向: 激光三维彩色数字成像、高光谱图像处理。
  • 基金资助:
    国家自然科学基金面上项目(61177002)。

Correction technique for color difference of multi-sensor texture

MA Qian1,2, GE Baozhen1,2, CHEN Lei1,2,3   

  1. 1. School of Precision Instrument and Opto-electronics Engineering, Tianjin University, Tianjin 300072, China;
    2. Key Laboratory of Opto-electronics Information and Technical Science of Ministry of Education(Tianjin University), Tianjin 300072, China;
    3. School of Information Engineering, Tianjin University of Commerce, Tianjin 300134, China
  • Received:2015-09-01 Revised:2015-10-25 Online:2016-04-10 Published:2016-04-08
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China(61177002).

摘要: 针对三维彩色扫描仪多个传感器获得的彩色纹理图像存在色彩差异,导致重建的三维彩色模型表面出现色彩分块现象的问题,提出一种基于色彩迁移的纹理图像色彩修正方法。首先,利用综合质量图像评价函数(CAF)进行图像质量评价,从多个传感器获得的彩色纹理图像中选出一幅质量最佳的作为标准图像;然后,参照该图像调整其他纹理图像各个色彩通道的色彩均值、方差等统计量。将所提方法用于三维人体彩色扫描仪的纹理图像色彩修正,结果表明,色彩修正后纹理图像间的色彩差异减小,得到的三维人体彩色模型色彩分块现象得到明显改善,色彩更加均衡自然。与经典色彩变换方法、改进色彩变换方法、基于最小角度选择的融合方法相比,实验的主观效果和客观图像综合质量评价值都表明了该方法的优越性。

关键词: 传感器, 纹理图像, 色彩差异修正, 三维人体彩色模型重建

Abstract: The texture images obtained by multiple sensors of 3D color scanner have color difference, resulting in color block in the 3D color model surface. In order to solve this problem, a modified method based on color transfer was proposed. First, the comprehensive assessment quality function was used to choose the best one of the color texture images obtained by multiple sensors as the standard image. Then, the mean and variance of other texture images in each color channel were adjusted refering to the standard image. The proposed method was applied to texture image color correction of 3D human body color scanner. The result shows that, after modifying the color difference between texture images, the color block of the color 3D body model is significantly improved with more balanced and natural color. Compared with the classical method, the improved color transformation method and the method based on the minimum angle selection method, the subjective and objective evaluation results prove the superiority of the proposed method.

Key words: sensor, texture image, color difference correction, 3D human color model reconstruction

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