期刊文献+

基于保边滤波器的单幅图像高光去除 被引量:1

Highlight Removal from Single Image Using Edge-Preserving Filter
下载PDF
导出
摘要 研究图像分割优化问题,由于图像中存在高光中,造成干扰,提出一种简单但有效的单幅图片高光去除方法。传统单幅图像高光去除方法,一般需要进行图像分割预处理,或者进行交互输入。提出的新方法无需图像分割预处理,也不要交互输入,而是使用漫反射色度估计值作为引导值,对最大色度图应用边界保留滤波器,并最终得到去高光后的图片。实验结果比较表明,与传统方法比较,该方法不但能够去除单色物体表面高光,对于复杂纹理表面高光非常有效,且输出图像在非高光区更接近输入图像,提高了图像分割效果。 This paper introduced a simple but effective method to remove highlight from a single given image. Tra- ditionally, image segmentation of preproeessing or interaction between human and computer is necessary for the elimi- nation of the highlight, however, it is not necessary to use our method. In this paper, a method based on the law that maximum diffuse chromaticity in local patch in any colorful image changes smoothly was introduced. To remove the highlight from the given image, an edge-reserve filter was applied to smooth the maximum chromaticity, with the approximation of maximum diffuse chromaticity applied as the smoothing guidance. Compared with a conventional method, it shows a better performance in removing the highlights existed in single-color images as well as heavy-tex- tured images, and the output image of the introduced method is closer to the input image in diffuse area.
出处 《计算机仿真》 CSCD 北大核心 2012年第11期316-318,354,共4页 Computer Simulation
关键词 高光去除 最大漫反射色度 保边滤波器 Highlight removal Maximum diffuse chromaticity Edge-reserve filter
  • 相关文献

参考文献10

  • 1S Shafer. Using color to separate re flection components[ J ]. Color Research & Application, 1985,10(4) :210-218.
  • 2Shree K Nayar, Fang Xi-Sheng and Terrance Bouh. Removal of Specularities Using Color and Polarization[ C]. Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition(CVPR93) , New York, USA, 1993:583-590.
  • 3S Lin, H Y Shum. Separation of diffuse and specular reflection in color images [ C ]. Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition ( CVPR 01 ), Kauai, USA, 2001: 341-346.
  • 4Xu Yiren, Wang Fujian, Zhao Yuming. Matching based Highlight Removal[C]. International Conference on Multimedia Technology (ICMT2010) Ningbo, CHINA, 2010 : 1-4.
  • 5Xu Yiren, Wang Fujian, Zhao Yuming. Matching based Highlight Removal[C]. International Conference on Multimedia Technology (ICMT2010) Ningbo, CHINA, 2010:1-4.
  • 6谭平,杨杰,雷蓓,Steve Lin,沈向洋.用于去除单张图像高光的光照约束补色[J].软件学报,2004,15(1):33-40. 被引量:14
  • 7R Tan, K Ikeuchi. Separating reflection components of textured surfaces using a single image [ J ]. IEEE Trans PAMI, 2005,27 (2) :178-193.
  • 8Pesal Koirala, Markku Hauta-Kasari, Parkkinen, Jussi. Highlight Removal from Single Image [ J ]. Lecture Notes in Computer Science: Springer Berlin/Heidelberg, 2009:176-187.
  • 9Q Yang, S Wang, N Ahuja. Real-time specular highlight removal using bilateral filtering[ C ]. Proceedings of the European Conference on Computer Vision ( ECCV 10) , Crete, Greece, 2010 : 87- 100.
  • 10K He, J Sun, X Tang. Guided image filtering[C]. Proceedings of the European Conference on Computer Vision (ECCV 10), Crete, Greece, 2010 : 1-14.

二级参考文献14

  • 1[1]Wolff LB. Using polarization to separate reflection components. In: Proc. of the IEEE Computer Vision and Pattern Recognition. 1989. 363~369.
  • 2[2]Sato Y, Ikeuchi K. Temporal-Color space analysis of reflection. Journal of the Optical Society of America A, 1994,11(11).
  • 3[3]Nayar SK, Fang X, Boult TE. Removal of specularities using color and polarization. In: Proc. of the IEEE Computer Vision and Pattern Recognition. 1993. 583~590.
  • 4[4]Klinker GJ, Shafer SA, Kanade T. The measurement of highlights in color images. International Journal of Computer Vision, 1990,2:7~32.
  • 5[5]Shafer SA. Using color to separate reflection components. COLOR Research and Application, 1985,10(4):210~218.
  • 6[6]Noak CL, Shafer SA. Anatomy of a color histogram. In: Proc. of the IEEE Computer Vision and Pattern Recognition. 1992. 599~605.
  • 7[7]Lee H-C. Method for computing the scene-illuminant chromaticity from specular highlights. Journal of the Optical Society of America A, 1986,1(10).
  • 8[8]Brainard DH, Freeman WT. Bayesian color constancy. Journal of the Optical Society of America A, 1997,14(7).
  • 9[9]Sapiro G. Color and illuminant voting. IEEE Trans. on Pattern Analysis and Machine Intelligence, 1999,21(11).
  • 10[10]Finlayson GD, Hordley SD, Hubel PM. Color by correlation: A simple, unifying framework for color constancy. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2001,23(11).

共引文献13

同被引文献1

引证文献1

二级引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部