Design and Realization of Airborne Embedded Image Enhancement System

YIN Chuan-li; WANG Xiao-zhe

doi:10.3788/YJYXS20132804.0604

您当前的位置：

首页 >

文章列表页 >

Design and Realization of Airborne Embedded Image Enhancement System

Imaging Technology & Image Processing | 更新时间：2020-08-12

- Design and Realization of Airborne Embedded Image Enhancement System
- Chinese Journal of Liquid Crystals and Displays Vol. 28, Issue 4, Pages: 604-607(2013)
- 作者机构：
  
  1. 中国科学院航空光学成像与测量重点实验室, 中国科学院长春光学精密机械与物理研究所,吉林长春,130033
  2. 清华大学电子工程系北京,100084
- 作者简介：
- 基金信息：
- DOI：10.3788/YJYXS20132804.0604
  CLC： TP391
- Received：20 November 2012，
  
  Revised：12 April 2013，
  
  Published：15 August 2013
- 稿件说明：
移动端阅览
尹传历, 王啸哲. 机载嵌入式图像增强系统设计与实现[J]. 液晶与显示, 2013,28(4): 604-607

YIN Chuan-li, WANG Xiao-zhe. Design and Realization of Airborne Embedded Image Enhancement System[J]. , 2013,28(4): 604-607
尹传历, 王啸哲. 机载嵌入式图像增强系统设计与实现[J]. 液晶与显示, 2013,28(4): 604-607 DOI： 10.3788/YJYXS20132804.0604.

YIN Chuan-li, WANG Xiao-zhe. Design and Realization of Airborne Embedded Image Enhancement System[J]. , 2013,28(4): 604-607 DOI： 10.3788/YJYXS20132804.0604.

摘要

针对传统直方图均衡化算法对比度增强容易过于强烈的缺点

提出了一种基于对比度有效控制的快速图像增强算法

首先统计直方图概率分布

计算平均亮度

然后采用自适应方法调整直方图分布

最后计算灰度转换公式

得到新灰度值。结合实际应用

以高性能DSP芯片TMS320C6455作为中央处理器

结合现场可编程门阵列FPGA构成外围电路逻辑控制

搭建了嵌入式高速图像增强处理平台。基于该平台用真实图像验证了文章提出的算法

实验结果表明

本系统增强图像整体画面自然

局部对比度明显

有效地防止了过度增强对比度带来的违和感

获得了较好的增强效果

同时算法处理简单

运算迅速

能够满足工程项目的要求。

Abstract

According to the disadvantage of too strongly contrast enhancement of traditional histogram equalization algorithm

a new image enhancement algorithm based on effective control of contrast was presented. First

the statistical histogram distribution and the ave-rage brightness were calculated. Then the histogram distribution is adjusted by the adaptive method. Finally the converting formula is calculated and the new bright values were obtained. An embedded high speed image enhancement processing system on high performance DSP TMS320DM6455 and FPGA was designed. Experimental results with real images showed that the system can naturally enhance overall image

the local contrast of the image is perfect

and the excessive sense of violation is prevented

and the process is simple

the running speed of the program is fast

so it can meet the requirements in the project.

关键词

Keywords

references

Zhai Y S, Liu X M. An improved fog-degraded image enhancement algorithm[C]//Wavelet Analysis and Pattern Recognition(ICWAPR),Beijing:IEEE ICWAPR, 2007:522-529.[2] 尹传历,张葆,戴明,等. 嵌入式雾天降质图像对比度增强系统的设计与实现 [J]. 电视技术, 2009, 33(12): 90-92.[3] Menotti D, Najman L. Multi-histogram equalization methods for contrast enhancement and brightness preserving [J].IEEE Trans. on Consumer Electronics, 2007, 53(3): 1186-1194.[4] 赵艳伟.基于图像分辨率增强算法的场景生成技术 [J]. 液晶与显示, 2001,26(6):823-830.[5] 黄梅,吴志勇,梁敏华,等.暗背景下低灰度图像的实时增强 [J]. 液晶与显示,2011, 26(3):374-378.[6] Tarel Jean-Philippe. Fast visibility restoration from a single color or gray level image[C]//2009 International Conference on Computer Vision(ICCV), Kvoto:IEEE ICCV,2009:20-28.[7] 尹传历. 基于双目立体视觉的三维测量技术研究[C]//长春:中科院长春光机所博士论文, 2008.[8] Zeyun. A fast and adaptive method for image contrast enhancement[C]//2004 International Conference on Image Processing, Singapore:IEEE ICIP, 2004:1001-1004.[9] Kim Joung-Youn,Kim Lee-Sup, Hwang Seung-Ho. An advanced contrast enhancement using partially overlapped Sub-Block Histogram Equalization[C]//IEEE Transactions on Circuits and Systems for Video Technology, New Jersey:IEEE Press Piscataway, 2001:475-484.[10] Yang Seungioon. Contrast enhancement using histogram equalization with bin underflow and bin overflow[C]// 2003 International Conference on Image Processing, Barcelona:IEEE ICIP,2003: 881-884.[11] 王彦臣,李树杰,黄廉卿. 基于多尺度Retinex的数字X光图像增强方法研究 [J]. 光学精密工程, 2006,14(1):70-76.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Embedded Image Enhancement System Based on Dark Channel Prior

Image enhancement algorithm based on global and local multi features

Underwater image enhancement algorithm based on improved color-line model

Sand-dust image enhancement based on Lab color space

Improved YOLOx-based vehicle detection method for low light environment

Related Author

YIN Chuan-li

SUN Li-na

HAN Song-wei

LIU Zhong-yu

LI Zhi-qiang

Yu-jie LIU

Shao-ping ZHU

LIANG Xiuman

Related Institution

Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences

Zhuhai City Polytechnic

College of Electrical Engineering， North China University of Science and Technology

Key Lab of Opt-Electronic Technology and Intelligent Control of Ministry of Education， Lanzhou Jiaotong University

Key Laboratory of Plateau Traffic Information Engineering and Control of Gansu Province， Lanzhou Jiaotong University

AI问答

Address：No.3888 Dong Nanhu Road, Changchun, Jilin, China 130033 Postal code：130033
Tel：0431-86176059 Email：yjxs@ciomp.ac.cn
Technical support is provided by Beijing Founder electronics co., LTD 吉ICP备11002662号-17 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰