文献知网节
  • 记笔记

Blind Deblurring of Single Car Image Based on Differential Autocorrelation and L-like Curve Method

Ke ZENGMu-rong JIANGYu LUOYu LUGuo-cai DU

School of Information Science and Engineering, Yunnan University

摘要:Blind deblurring of single image is an inverse problem in the field of image processing. Its difficulty lies in the non-uniqueness of the inverse process. The regularization method is a classical algorithm for blind deblurring of images, it can iteratively solve blur kernel and clear image by constructing regularization terms. However, improper values of regularization parameter and blur kernel size can easily lead to poor inverse results. In this paper, by calculating differential autocorrelation of the image to obtain the blur scale as the blur kernel size. Then, we proposed a L-like curve method to calculate the regularization parameter. Finally, these calculation results were used to deblur the image with the regularization model. The experimental results show that the proposed method can effectively achieve blind deblurring of images, and the inverse effect of a single blurred car image is obvious. It can meet the requirements of accurately identifying the license plate information of blurred car image.
会议名称:

2019 International Conference on Energy, Power, Environment and Computer Application(ICEPECA 2019)

会议时间:

2019-01-20

会议地点:

中国湖北武汉

  • 专辑:

    信息科技

  • 专题:

    计算机软件及计算机应用

  • 分类号:

    TP391.41

  • 手机阅读
    即刻使用手机阅读
    第一步

    扫描二维码下载

    "移动知网-全球学术快报"客户端

    第二步

    打开“全球学术快报”

    点击首页左上角的扫描图标

    第三步

    扫描二维码

    手机同步阅读本篇文献

  • CAJ下载
  • PDF下载

下载手机APP用APP扫此码同步阅读该篇文章

下载:2 页码:424-431 页数:8 大小:1294k

引文网络
  • 参考文献
  • 引证文献
  • 共引文献
  • 同被引文献
  • 二级参考文献
  • 二级引证文献
  • 批量下载
相关推荐
  • 相似文献
  • 读者推荐
  • 相关基金文献
  • 相关法规
  • 关联作者
  • 相关视频