计算机科学 ›› 2014, Vol. 41 ›› Issue (12): 245-250.doi: 10.11896/j.issn.1002-137X.2014.12.053

• 图形图像与模式识别 • 上一篇    下一篇

基于多峰高斯函数的直方图规定化算法

赵通,王国胤,肖斌   

  1. 重庆邮电大学计算智能重庆市重点实验室 重庆400065重庆邮电大学计算机科学与技术研究所 重庆400065;重庆邮电大学计算智能重庆市重点实验室 重庆400065重庆邮电大学计算机科学与技术研究所 重庆400065;重庆邮电大学计算智能重庆市重点实验室 重庆400065重庆邮电大学计算机科学与技术研究所 重庆400065
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受国家自然科学基金项目:不确定性概念内涵与外延的双向认知计算理论模型与方法(61272060),国家自然科学基金项目:退化图像不变性识别(61201383),重庆市基础与前沿研究计划重点项目:计算认知理论模型与方法研究(cstc2013jjB40003),重庆市基础与前沿项目:退化图像不变特征构造与识别研究(cstc2013jcyjA40048)资助

Image Specification Algorithm Based on Multi-peaks Gaussian Function

ZHAO Tong,WANG Guo-yin and XIAO Bin   

  • Online:2018-11-14 Published:2018-11-14

摘要: 直方图均衡化作为一种特殊的直方图规定化方法,能有效地增强图像的对比度,但其对直方图活动范围的拉伸通常会造成图像过度增强。一种基于高斯函数的直方图规定化算法可提高控制对比度活动范围的能力,然而该算法处理的图像缺乏层次感。基于此,提出一种基于多峰高斯函数的直方图规定化算法,该算法首先用直方图求导方法估算出原直方图的局部峰值和方差,从而得到原直方图的多峰高斯函数,然后采用扩展后的多峰高斯函数作为目的直方图进行规定化。此算法的主要特点是改变局部峰的参数,有选择地对某局部灰度范围进行对比度增强,从而拉伸整个图像对比度的活动范围。对于彩色图像增强,该算法在对彩色图像R,G,B 3个分量子图直方图规定化处理的基础上,根据人类视觉习惯,引入彩色恢复因子将规定化的R,G,B分量进行有效合并。实验结果和原理分析表明,该算法能有效增强图像的视觉效果,使其细节明晰,层次丰富。

关键词: 图像增强,直方图均衡化,多峰高斯函数,求导,直方图规定化,色彩恢复因子

Abstract: Histogram equalization,as a special histogram specification method,is an effective algorithm for image contrast enhancement.But it stretches the dynamic range of the image’s histogram which usually makes some of the uniform regions of the output image become saturated with high light.An image specification algorithm based on Gaussian PDF has been proposed recently.However,it is unsatisfactory for image enhancement due to its worse sense of hierarchy.Based on this,an image specification algorithm based on multi-peaks Gaussian function was proposed in this paper.In this form,local-means and local-variances can be estimated respectively with the method of derivative.A key feature of the algorithm is that varying the parameters of local-variances can enhance the image contrast selectively and locally.The resulting process can broaden a range of image contrast.For color image enhancement,the proposed algorithm can be the provisions of the R,G,B three sub image of color image and then effectively combine R,G and B with the color recovery factor on the habit of human vision.Both experimental results and theoretical analysis demonstrate the proposed algorithm is optical effective.

Key words: Image enhancement,Histogram equalization,Multi-peaks Gaussian function,Derivation,Histogram specification,Color recovery factor

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