期刊文献+

基于BP神经网络和逆滤波器的小波域半盲离焦图像复原(英文) 被引量:4

Semi-blind defocused image rstoration using BP network andinverse filterin wavelet domain
下载PDF
导出
摘要 本文利用BP神经网络和逆滤波器提出了一种新的半盲离焦图像复原算法.在小波域,提取特点向量,然后训练BP神经网络,利用训练后的网络估计离焦参数.根据离焦参数得到点扩展函数,利用逆滤波器复原模糊图像.仿真实验结果表明:该方法能有效地复原离焦模糊图像. A novel semi-blind defocused image restoration technique is proposed, which is based on back propagation(BP) neural network and inverse filtering. In this technique, firstly a BP neural network is trained in wavelet domain to estimate defocus parameter. After obtaining the point spread function (PSF) parameter, inverse filter is adopted to complete the restoration. We experimentally illustrate its performance on simulated data. Results show that the proposed PSF parameter estimation technique is effective.
出处 《四川大学学报(自然科学版)》 CAS CSCD 北大核心 2007年第1期47-53,共7页 Journal of Sichuan University(Natural Science Edition)
基金 四川省科技厅应用基础研究项目(2006J13-092)
关键词 离焦图像复原 小波变换 BP神经网络 逆滤波器 defocused image restoration, wavelet transform, back propagation(BP) neural network, inverse filtering
  • 相关文献

参考文献10

  • 1Chen W F,Chen M,Zlaou J. Adaptively regularized constrained total least-squares image restoration [J]. IEEE Trans on Image Processing,2000,9(4) :588.
  • 2Awate S P, Whitaker R T. Unsupersived, informationtheoretic, adaptive image filtering for image restoration[J]. IEEE Trans on Pattern Analysis and Machine Intellgence, 2006,28 (3): 364.
  • 3Flusser F S J. Muhichannel blind iterative image restoration [J]. IEEE Trans on Image Processing, 2003,12(9) :1094.
  • 4Figuelredo M A T, Nowak R D. An EM algorithm for wavelet-based image restoration [J]. IEEE Trans on Image Proeesslng, 2003,12(8): 906.
  • 5Liao Y H, Lin X Y. Blind image restoration with Eigen-Face subspace [J]. IEEE Trans on Image Processing,2005,14 (11): 1766.
  • 6Chang M M,Tekalp A M,Erdem A T. Blur identification using the bi-spectrum [J]. IEEE Trans on Image Processing, 1991,39(10):2323.
  • 7Reeves S J, Mersereau R M. Blur identification by the method of generalized cross-validation [J]. IEEE Trans on Image Processing, 1992,1 (7): 301.
  • 8Lagendijk R L,Biemond J,Boekee B E. Identification and restoration of noisy blurred images using the expectationmaximization algorithm [J]. IEEE Trans on Acoustics,Speech,Signal Processing,1990,38(7):1180.
  • 9Kundur D, Hatzinakos D. A novel blind deconvolution scheme for image restoration using recurisive faltering[J]. IEEE Trans on Signal Processing, 1998,46(2):375.
  • 10Katsaggdos A K, Lay K T. Maximum likelihood blur identification and image restoration using the EM algorithm [J]. IEEE Trans on Signal Processing, 1991,39(3) :729.

同被引文献20

引证文献4

二级引证文献7

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部