应用参数化对数模型增强图像细节及对比度

朱瑞飞; 贾宏光; 王超; 魏群; 张天翼; 虞林瑶

doi:10.3788/OPE.20142204.1064

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应用参数化对数模型增强图像细节及对比度

信息科学 | 更新时间：2020-08-13

- 应用参数化对数模型增强图像细节及对比度
- Enhancement of image detail and contrast by parameterized logarithmic framework
- 光学精密工程 2014年22卷第4期页码：1064-1070
- 作者机构：
  
  1. 中国科学院长春光学精密机械与物理研究所,吉林长春,中国,130033
  2. 中国科学院大学北京,中国,100049
- 作者简介：
- 基金信息：
  
  中国科学院三期创新工程装备预研基金资助项目（No.51301060207）()
- DOI：10.3788/OPE.20142204.1064
  中图分类号： TN219;TP391
- 收稿日期：2013-04-24，
  
  修回日期：2013-06-12，
  
  纸质出版日期：2014-04-25
- 稿件说明：
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朱瑞飞, 贾宏光, 王超等. 应用参数化对数模型增强图像细节及对比度[J]. 光学精密工程, 2014,22(4): 1064-1070

ZHU Rei-fei, JIA Hong-guang, WANG Chao etc. Enhancement of image detail and contrast by parameterized logarithmic framework[J]. Editorial Office of Optics and Precision Engineering, 2014,22(4): 1064-1070
朱瑞飞, 贾宏光, 王超等. 应用参数化对数模型增强图像细节及对比度[J]. 光学精密工程, 2014,22(4): 1064-1070 DOI： 10.3788/OPE.20142204.1064.

ZHU Rei-fei, JIA Hong-guang, WANG Chao etc. Enhancement of image detail and contrast by parameterized logarithmic framework[J]. Editorial Office of Optics and Precision Engineering, 2014,22(4): 1064-1070 DOI： 10.3788/OPE.20142204.1064.

摘要

传统红外图像增强方法由于未考虑人眼视觉特性而存在"超区间值"，故极易丢失图像细节。本文结合对数图像处理（LIP）理论，提出了基于参数化对数模型（PLIP）的平台直方图均衡图像增强方法。该方法首先将图像变换为灰度色调函数；然后应用PLIP模型对变换后的图像进行重建，结合平台直方图均衡化来增强图像的对比度和细节信息，并利用图像评价函数（EMEE）与信息熵（En）确定模型的参数值。最后，研制了算法硬件平台，分别用中波和长波红外成像系统对算法进行了实验验证。实验结果显示：该方法对不同场景的图像均可取得很好的增强效果，图像的EMEE值比传统的平台直方图均衡算法提高至少5倍以上，对改善图像质量和视觉效果具有实用价值。

Abstract

The traditional infrared image enhancing has "over range value" caused by not taking vision characters of human eye into consideration

therefore

image details are lost. In this paper

an enhanced algorithm based on Parameterized Logarithmic Image Pocessing(PLIP) model was proposed for histogram equalization image processing. First

the image was converted to a gray tone function. Then

the image was reconstructed by the PLIP model and its contrast and details were enhanced by combined plateau histogram equalization. The model parameters were determined by evaluation of function (Measurement of Enhancement by Entropy

EMEE) and information entropy (En). Finally

the hardware platform of the algorithm was developed

and the algorithm was verified respectively by the medium-wave and long-wave infrared image systems. Experimental results show that the method can obtain better enhanced effect for different images. The EMEE of the enhanced image is more than 5 times than traditional plateau histogram equalization algorithm. The results show that this method has an application value to improve the image quality and visual effect.

关键词

Keywords

references

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