浏览全部资源
扫码关注微信
1. 中南大学 信息科学与工程学院,湖南 长沙,410081
2. 湖南第一师范学院 信息科学与工程学院,湖南 长沙,410205
收稿日期:2015-01-09,
修回日期:2015-03-06,
纸质出版日期:2015-07-25
移动端阅览
廖永忠, 蔡自兴, 何湘华. 应用半二次罚函数的图像盲去模糊[J]. 光学精密工程, 2015,23(7): 2086-2092
LIAO Yong-zhong, CAI Zi-xing, HE Xiang-hua. Image blind deblurring with half-quadratic penalty method[J]. Editorial Office of Optics and Precision Engineering, 2015,23(7): 2086-2092
廖永忠, 蔡自兴, 何湘华. 应用半二次罚函数的图像盲去模糊[J]. 光学精密工程, 2015,23(7): 2086-2092 DOI: 10.3788/OPE.20152307.2086.
LIAO Yong-zhong, CAI Zi-xing, HE Xiang-hua. Image blind deblurring with half-quadratic penalty method[J]. Editorial Office of Optics and Precision Engineering, 2015,23(7): 2086-2092 DOI: 10.3788/OPE.20152307.2086.
由于现有的模糊图像盲恢复算法计算复杂度高
计算量大
本文提出了一种基于半二次罚函数的图像盲去模糊算法
并进行了实验验证。应用图像噪声的多阶偏导数的高斯分布特性和图像梯度值服从hyper-Laplacian分布特性建立方程
使用高效交替迭代的算法对方程求解。由于迭代过程中采用快速傅里叶变换一次求解
故大大降低了运算时间
同时获得了很好的恢复效果
为实现实时视频图像去模糊奠定了基础。对一个百万像素级的图像进行了去模糊实验
结果显示
本文算法比当前流行的算法有更快的计算速度和更好的鲁棒性
计算时间缩短了60% 。提出的算法为视频图像的实时盲恢复提供了新的工具。
As existing image blind deblurring algorithms have larger and more complex computing
this paper proposes a new image blind deblurring algorithm based on half-quadratic penalty method
and verifies the feasibility of the algorithm by experiments. It formulates the optimization function by using the higher-order partial derivatives of image noise and the hyper-Laplacian priors of image gradients
then uses an efficient optimization scheme that alternates between PSF and latent image estimation to solve the proposed formula. As the fast Fourier transform has been used in iterative processing
the computing time is reduced greatly
and the restoration effects are improved. An debluring experimental is performed on an image with pixel levels of 1×10
6
and the results demonstrate that the proposed method is more robust and more computationally efficiency than that of current blind deblurring algorithm and its computing time has been reduced by about 60%. The algorithm provides a new way for blind deblurring of video images in real time.
PAN J SH, HU ZH, SU ZH X, et al.. Deblurring text images via L0-regularized intensity and gradient prior[C]. Computer Vision and Pattern Recognition (CVPR), 2014,2901-2908.
HE N, LU K, BAO B K, et al.. Single-image motion deblurring using an adaptive image prior [J]. Information Sciences, 2014, 281: 736-749.
SROUBEK F, MILANFAR P. Robust multichannel blind deconvolution via fast alternating minimization[J]. IEEE Transactions on Image Processing, 2012, 21(4): 1687-1700.
LEVIN A, WEISS Y, DURAND F, et al.. Efficient marginal likelihood optimization in blind deconvolution[C].2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011: 2657-2664.
LEVIN A, WEISS Y, DURAND F, et al.. Understanding and evaluating blind deconvolution algorithms[C].Computer Vision and Pattern Recognition, 2009: 1964-1971.
CHO T S, PARIS S, HORN B K P, et al.. Blur kernel estimation using the radon transform[C].2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011: 241-248.
Krishnan D, Tay T, Fergus R. Blind deconvolution using a normalized sparsity measure[C].Computer Vision and Pattern Recognition (CVPR), 2011: 233-240.
BAE H, FOWLKES C C, CHOU P H. Patch Mosaic for Fast Motion Deblurring[M].Computer Vision-ACCV 2012. Springer Berlin Heidelberg, 2013: 322-335.
ZHONG L, CHO S, METAXAS D, et al.. Handling noise in single image deblurring using directional filters[C].In Proc. of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2013: 612-619.
PERRONE D, FAVARO P. Total variation blind deconvolution: The devil is in the details[C].IEEE International Conference on Computer Vision and Pattern Recognition, 2014: 2909-2916.
OLIVEIRA J P, FIGUEIREDO M A T, BIOUCAS-Dias J M. Parametric blur estimation for blind restoration of natural images: Linear motion and out-of-focus [J]. IEEE Transactions on Image Processing, 2014, 23(1): 466-477.
廖永忠,蔡自兴,何湘华. 运动模糊图像盲解卷积的快速算法[J]. 光学 精密工程,2013, 21(10): 2688-2695. LIAO Y ZH,CAI Z X,HE X H. Fast algorithm for motion blurred image blind deconvolution [J].Opt. Precision Eng.,2013, 21(10): 2688-2695.
SIMON M K. Probability Distributions Involving Gaussian Random Variables: A Handbook for Engineers and Scientists[M]. Norwell:Academic Publishers, 2007.
SIMONCELLI E P. Bayesian Denoising of Visual Images in the Wavelet Domain[M]. New York: Bayesian inference in wavelet-based models, 1999: 291-308.
FERGUS R,SINGH B,HERTZMANN A,et al.. Removing camera shake from a single photograph[C].SIGGRAPH, 2006:787-794.
GEMAN D, YANG C. Nonlinear image recovery with half-quadratic regularization[J]. IEEE Transactions on Image Processing, 1995, 4(7): 932-946.
WANG Y, YANG J, YIN W, et al.. A new alternating minimization algorithm for total variation image reconstruction[J]. SIAM Journal on Imaging Sciences, 2008, 1(3): 248-272.
YIN W, OSHER S, GOLDFARB D, et al.. Bregman iterative algorithms for \\ell_1-minimization with applications to compressed sensing[J]. 2008, 1(1): 143-168.
BECK A, TEBOULLE M. A fast iterative shrinkage-thresholding algorithm for linear inverse problems[J]. SIAM Journal on Imaging Sciences, 2009, 2(1): 183-202.
KRISHNAN D, FERGUS R. Fast image deconvolution using hyper-Laplacian priors[J]. Advances in Neural Information Processing Systems, 2009, 22: 1-9.
SHAN Q, JIA J, AGARWALA A. High-quality motion deblurring from a single image.ACM Transactions on Graphics (TOG), 2008, 27(3): 73.
0
浏览量
457
下载量
1
CSCD
关联资源
相关文章
相关作者
相关机构