吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (04): 1133-1138.doi: 10.7964/jdxbgxb201304046

• 论文 • 上一篇    下一篇

水下模糊图像参数估计复原方法

李一兵, 付强, 张静   

  1. 哈尔滨工程大学 信息与通信工程学院,哈尔滨 150001
  • 收稿日期:2012-07-11 出版日期:2013-07-01 发布日期:2013-07-01
  • 通讯作者: 付强(1988-),男,博士研究生.研究方向:数字图像处理.E-mail:funq2012@hotmail.com E-mail:funq2012@hotmail.com
  • 作者简介:李一兵(1967-),男,教授,博士生导师.研究方向:超宽带信号检测与处理,数字图像处理,信息融合技术.E-mail:liyibing0920@sina.cn
  • 基金资助:

    船舶工业国防科技预研项目(10J3.1.6); "973"国家高技术研究发展计划项目(61393010101-1).

Underwater blurred image restoration based on parameter estimation

LI Yi-bing, FU Qiang, ZHANG Jing   

  1. College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
  • Received:2012-07-11 Online:2013-07-01 Published:2013-07-01

摘要:

针对不同的图像退化模型,分析了图像模糊的不同类型以及通过解卷积复原图像的各类方法,讨论了对应于不同模糊类型所适用的解卷积方法。在对水下图像复原前先采取去噪预处理较好地抑制了复原过程的病态问题,再利用拉东变换和傅里叶变换估计点扩展函数中模糊角度和模糊距离,实现了在缺少先验信息前提下的水下图像的复原,且相比于其他估计方法更加简便准确。实验结果表明:该方法能较为有效地复原水下模糊图像。

关键词: 信息处理技术, 图像复原, 模糊类型, 参数估计, 拉东变换

Abstract:

This paper analyzes various image restoration methods for different image degradation models and discusses how to apply deconvolution to match suitable blur model first. Then, on these bases, a new method with denoising preprocessing is proposed to realize underwater image restoration without prior information. The proposed method considers the Radon transform and Fourier transform to estimate the fuzzy angle and distance in the Point Spread Function (PSF), which is simpler and more precise than other estimation methods. Simulation results show that this denoising preprocessing could inhibit the ill-posed problem of image restoration process, thus the proposed method can greatly improve the image quality and definition.

Key words: information processing, image restoration, blur type, parameter estimation, Radon transform

中图分类号: 

  • TN911.73

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