计算机科学 ›› 2017, Vol. 44 ›› Issue (Z6): 179-182.doi: 10.11896/j.issn.1002-137X.2017.6A.041

• 模式识别与图像处理 • 上一篇    下一篇

基于双树复小波的图像修复

窦立云,徐丹,李杰,陈浩,刘义成   

  1. 云南大学信息学院 昆明650500,云南大学信息学院 昆明650500,云南大学信息学院 昆明650500,云南大学信息学院 昆明650500,云南大学信息学院 昆明650500
  • 出版日期:2017-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金资助

Image Inpainting Based on Dual-tree Complex Wavelet Transform

DOU Li-yun, XU Dan, LI Jie, CHEN Hao and LIU Yi-cheng   

  • Online:2017-12-01 Published:2018-12-01

摘要: 小波变换技术已被广泛应用于图像修复领域,但其在图像修复过程中出现的边缘部分模糊或不连接的情况成为了一个难点。针对此问题,提出了基于双树复小波变换的图像修复算法。该算法使用双树复小波变换对破损图像进行多尺度和多方向的分解,对各个高频方向子带使用全变分(Total Variation,TV)模型进行快速修复,各个低频分量使用改进了的曲率驱动扩散(Curvature-Driven-Diffusions,CCD)模型进行迭代修复,最后通过小波逆变换得到最终的修复图像。实验结果表明,该方法很好地推广了双树复小波变换在图像修复领域中的应用,并且在图像纹理的修复以及在结构部分的填充都有较好的效果。

关键词: 图像修复,双树复小波,多尺度分解,全变分模型,曲率驱动扩散

Abstract: The wavelet transform technology has been widely used in the field of digital image inpainting,however,the image inpainting based on wavelet transform will appear the phenomenon of edge fuzzy and not connection,which becomes a difficult problem.Based on the multiscale and multidirectional decomposition and the traditional method of ima-ge inpainting,a new algorithm of image inpainting based on dual-tree complex wavelet transform was proposed.Firstly,the image is decomposed into low frequency and high frequency parts by using the dual-tree complex wavelet transform.Then the parts of different frequency after image decomposition are inpainted respectively.The high frequency components of the image are inpainted by the total variation model,and an improved curvature-driven-diffusion is used to repair the low frequency components.Finally,the final image is obtained by dual-tree complex wavelet transform reconstruction process.The experimental results show that the proposed algorithm is very good for the promotion of the dual-tree complex wavelet transform in image inpainting application and gets better repair both in the part of texture and the part of structure.

Key words: Image inpainting,Dual-tree complex wavelet,Multi-scale decomposiyion,Total variation model,Curvature-driven-diffusions

[1] BERTALMIO M,SAPIRO G,CASELLES V.Image inpainting[C]∥Conference on Computer Graphics and Interactive Techniques.ACM Press/Addison-Wesley Publishing Co.,2002:417-424.
[2] CHAN T F,SHEN J.NontextureInpainting by Curvature-DrivenDiffusions[J].Journal of Visual Communication & Image Representation,2001,12(4):436-449.
[3] RUDIN L I,OSHER S,FATEMI E.Nonlinear total variation based noise removal algorithms [J].Physica D Nonlinear Phenomena,1992,60(1-4):259-268.
[4] CHAN T F,KANG S H,SHEN J.Euler’s elastica and curvature based inpainting[J].SIAM Journal on Applied Mathemati-cs,2002,63(2):564-592.
[5] TSAI A,YEZZI A R,WILLSKY A S.Curve evolution implementation of the Mumford-Shah functional for image segmentation,denoising,interpolation,and magnification[J].IEEE Tran-sactions on Image Processing,2001,10(8):1169-1186.
[6] ESEDOGLU S,SHEN J.Digital Inpainting Based On The Mumford-Shah-Euler Image Model[J].European Journal of Applied Mathematics,2002,13(4):353-370.
[7] CRIMINISI A,PEREZ P,TOYAMA K.Object Removal byExemplar-Based Inpainting[C]∥IEEE Computer Society Con-ference on Computer Vision & Pattern Recognition.2003:721-728.
[8] WEXLER Y,SHECHTMAN E,IRANI M.Space-time completion of video[J].IEEE Transactions on Pattern Analysis & Machine Intelligence,2007,29(3):463-476.
[9] BUGEAU A,BERTALMO M,CASELLES V,et al.A comprehensive framework for image inpainting[J].IEEE Transactions on Image Processing A Publication of the IEEE Signal Proces-sing Society,2010,19(10):2634-2645.
[10] 孟春芝,何凯,焦青兰.自适应样本块大小的图像修复方法[J].中国图象图形学报,2012,17(3):337-341.
[11] 李志丹,和红杰,尹忠科.基于块结构稀疏度的自适应图像修复算法[J].电子学报,2013,41(3):549-554.
[12] RAN L,MENG X.Fast Seam Carving Using Gaussian Pyramid[C]∥2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC).IEEE,2014:59-63.
[13] REN S,LEI J,ZHANG T,et al.Research of High Performance Information Hiding Scheme Based on Gaussian Pyramid and CARDBAL2 multi-wavelet for Secret Communication[J].International Journal of Applied Mathematics & StatisticsTM,2014,52(6):243-251.
[14] 廖斌,苏涛,刘斌.基于多尺度分解的邻域随机查找快速图像修复[J].电子与信息学报,2015,37(9):2097-2102.
[15] ZHANG H,DAI S.Image Inpainting Based on Wavelet Decomposition[J].Procedia Engineering,2012,29(4):3674-3678.
[16] 张东,唐向宏,张少鹏,等.小波变换与纹理合成相结合的图像修复[J].中国图象图形学报,2015,20(7):882-894.
[17] 石宏理,胡波.双树复小波变换及其应用综述[J].信息与电子工程,2007,5(3):229-234.
[18] KINGSBURY N.The dual-tree complex wavelet transform:Anew efficient tool for image restoration and enhancement[C]∥Signal Processing Conference.IEEE,1998:319-322.
[19] KINGSBURY N.Complex Wavelets for Shift Invariant Analysis and Filtering of Signals[J].Applied & Computational Harmonic Analysis,2001,10(3):234-253.
[20] SELESNICK I W,Baraniuk R G,Kingsbury N G.The dual-tree complex wavelet transform[J].IEEE Signal Processing Magazine,2005,22(6):123-151.
[21] 吴一全,宋昱.基于双树复小波域HMT模型的煤燃烧火焰图像去噪[J].华南理工大学学报(自然科学版),2014,42(1):59-65.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!