中国科学院光电技术研究所机构知识库
Advanced  
IOE OpenIR  > 光电探测与信号处理研究室(五室)  > 会议论文
题名:
An efficiency restoration method for turbulence-degraded image base on improved SeDDaRA method
作者: Zuo Haorui; Zhang Qihen; Zhao Rujin
出版日期: 2009
会议名称: Proceedings of SPIE
会议日期: 2009
通讯作者: Zuo Haorui
中文摘要: Turbulence-degraded image restoration is an important part in detection system which based on image. Most of current researches on turbulence-degraded image were focus on getting perfect image and not very care about processing speed. They are not acceptable when they apply on a real-time detection system. In order to restore degraded image clearly and rapidly, in this paper we introduce an efficiency restoration method for turbulence-degraded image base on improved SeDDaRA (self-deconvolving data reconstruction algorithm) method. SeDDaRA transform the image data form space field to spectrum field and smooth image's spectrum data and use a power law relation applied to the smoothed spectrum data to extract a filter function. This filter function can be used to restore and enhance higher-frequency content and get the system's Point Spread Function (PSF). The PSF can be used for deconvolution filter such as Winner and nonnegative least squares to restore the image. There are three major contributions in this paper. Firstly, we add a pre-denoise process to remove the noise which introduced by system such as period noise and Gauss noise. This step can significant improve the restore image's quality. Secondly we use an optimum method to extract the filter function which responded to PSF. The method, based on spectrum's power law characteristic, only need compute 8-direction date of the whole data to get the parameter. Compared with normal SeDDaRA method which need compute all data in spectrum field the new method can significant reduce the compute complication. Thirdly we utilize image's inherent characteristic and introduce a novel method to estimation deconvolution filter's SNR. The accurate SNR can efficiently improve the restoration quality. Compared with other restoration method, our method is noniterative and requires only that the point-spread function be space invariant and the transfer function be real. These mean that our method can work efficiently and requires little knowledge of the original data or the degradation. Experiments on real turbulence-degraded image indicate that the proposed method is very fast and can get quality restore image, which demonstrates the feasibility and validity of the proposed method.
英文摘要: Turbulence-degraded image restoration is an important part in detection system which based on image. Most of current researches on turbulence-degraded image were focus on getting perfect image and not very care about processing speed. They are not acceptable when they apply on a real-time detection system. In order to restore degraded image clearly and rapidly, in this paper we introduce an efficiency restoration method for turbulence-degraded image base on improved SeDDaRA (self-deconvolving data reconstruction algorithm) method. SeDDaRA transform the image data form space field to spectrum field and smooth image's spectrum data and use a power law relation applied to the smoothed spectrum data to extract a filter function. This filter function can be used to restore and enhance higher-frequency content and get the system's Point Spread Function (PSF). The PSF can be used for deconvolution filter such as Winner and nonnegative least squares to restore the image. There are three major contributions in this paper. Firstly, we add a pre-denoise process to remove the noise which introduced by system such as period noise and Gauss noise. This step can significant improve the restore image's quality. Secondly we use an optimum method to extract the filter function which responded to PSF. The method, based on spectrum's power law characteristic, only need compute 8-direction date of the whole data to get the parameter. Compared with normal SeDDaRA method which need compute all data in spectrum field the new method can significant reduce the compute complication. Thirdly we utilize image's inherent characteristic and introduce a novel method to estimation deconvolution filter's SNR. The accurate SNR can efficiently improve the restoration quality. Compared with other restoration method, our method is noniterative and requires only that the point-spread function be space invariant and the transfer function be real. These mean that our method can work efficiently and requires little knowledge of the original data or the degradation. Experiments on real turbulence-degraded image indicate that the proposed method is very fast and can get quality restore image, which demonstrates the feasibility and validity of the proposed method.
收录类别: Ei
语种: 英语
卷号: 7383
文章类型: 会议论文
内容类型: 会议论文
URI标识: http://ir.ioe.ac.cn/handle/181551/7682
Appears in Collections:光电探测与信号处理研究室(五室)_会议论文

Files in This Item:
File Name/ File Size Content Type Version Access License
2009-254.pdf(1332KB)会议论文--限制开放View 联系获取全文

作者单位: 中国科学院光电技术研究所

Recommended Citation:
Zuo Haorui,Zhang Qihen,Zhao Rujin. An efficiency restoration method for turbulence-degraded image base on improved SeDDaRA method[C]. 见:Proceedings of SPIE. 2009.
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Zuo Haorui]'s Articles
[Zhang Qihen]'s Articles
[Zhao Rujin]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Zuo Haorui]‘s Articles
[Zhang Qihen]‘s Articles
[Zhao Rujin]‘s Articles
Related Copyright Policies
Null
Social Bookmarking
Add to CiteULike Add to Connotea Add to Del.icio.us Add to Digg Add to Reddit
文件名: 2009-254.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 
评注功能仅针对注册用户开放,请您登录
您对该条目有什么异议,请填写以下表单,管理员会尽快联系您。
内 容:
Email:  *
单位:
验证码:   刷新
您在IR的使用过程中有什么好的想法或者建议可以反馈给我们。
标 题:
 *
内 容:
Email:  *
验证码:   刷新

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.

 

 

Valid XHTML 1.0!
Copyright © 2007-2016  中国科学院光电技术研究所 - Feedback
Powered by CSpace