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山东大学学报(理学版) ›› 2016, Vol. 51 ›› Issue (1): 101-105.doi: 10.6040/j.issn.1671-9352.0.2015.357

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基于层级分割的颜色恒常性算法

王磊1,谢江宁2   

  1. 1.潍坊学院计算机工程学院, 山东 潍坊 261061;2.山东大学计算机科学与技术学院, 山东 济南 250101
  • 收稿日期:2015-07-21 出版日期:2016-01-16 发布日期:2016-11-29
  • 作者简介:王磊(1982— ),男,讲师,研究方向为图形图像处理、计算机视觉和软件工程. E-mail:wanglpqpq@gmail.com

Color constancy using hierarchy segments

WANG Lei1, XIE Jiang-ning2   

  1. 1. School of Computer Engineering, Weifang University, Weifang 261061, Shandong, China;
    2. School of Computer Science and Technology, Shandong University, Jinan 250101, Shandong, China
  • Received:2015-07-21 Online:2016-01-16 Published:2016-11-29

摘要: 颜色恒常性是指当照射物体表面的颜色光发生变化时,人们对该物体表面颜色的知觉仍然保持不变的视觉特性。灰度世界方法是一种常用的的颜色恒常方法,它假设客观世界中物体表面的平均反射比趋于灰色(灰度世界假设)。传统的灰度世界方法对整幅图像进行处理,然而并不是所有的图像都满足灰度世界假设。首先采用层级分割方法把图像分割成若干个片段,然后采用使用灰度世界方法处理各个片段,得到各个片段的估计结果;最后对这些估计结果进行聚类,得到最终结果。实验结果表明,该方法优于原始的灰度世界方法。与原始方法相比,平均误差降低至36.0%、中值误差降低至63.5%。本文所提出的算法优于目前领先的颜色恒常算法。

关键词: 贝叶斯方法, 层次分割, 图像分割, 颜色恒常性

Abstract: Color constancy is the ability to measure colors of objects independent of the color of the light source. A well-known color constancy method is based on the gray-world assumption which assumes that the average reflectance of surfaces in the world is achromatic. In this paper, instead of applying gray world method on the entire image, the images was segment into a lot of segments using a hierarchical segmentation method, and the simple gray world approach was applied on each segments. Then, estimated results from different segments were clustered together to get a final result. Experiment results show that the proposed algorithm outperforms the original gray world method. The mean error is reduced to 36.0% with respect to the original gray world method and the median error is reduced to 63.5%. Our method outperforms state-of-the-art color constancy algorithms and produces comparable results with the best published scores on the same dataset.

Key words: hierarchy segments, Bayes, color constancy, image segments

中图分类号: 

  • TP391
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