基于对数运算以及附加方向梯度算子的总变分修复算法
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摘要
总变分修复算法在去除图像划痕和文本时需要较多迭代,对边缘细节信息的保持性不理想,并且存在阶梯效应,修复后的图像峰值信噪比较低。针对这些缺陷,提出了改进的算法,在原算法正则项中加入对数运算以及附加方向梯度算子,从而避免了阶梯效应,减少了迭代次数,降低了图像在边缘细节处的平滑力度。仿真结果证明,改进的算法减少了迭代次数,并且可以很好地保留图像的细节信息,所修复的图像具有很好的视觉效果。
The total variation image inpainting algorithm needs more iterations to remove the text and scratches.It is not ideal for the preservation of edge details,and has a staircase effect.The peak signal to noise ratio of the restored image is relatively low.Aiming at these defects,an improved algorithm is proposed.The logarithmic operation and additional directional gradient operator are added into the regular term of the original algorithm to avoid the staircase effect,reduce the number of iterations,and reduce the smoothing of image at edge details.Simulation results show that the improved algorithm reduces the number of iterations retains the details of the image,well and the restored image has good visual effect.
The total variation image inpainting algorithm needs more iterations to remove the text and scratches.It is not ideal for the preservation of edge details,and has a staircase effect.The peak signal to noise ratio of the restored image is relatively low.Aiming at these defects,an improved algorithm is proposed.The logarithmic operation and additional directional gradient operator are added into the regular term of the original algorithm to avoid the staircase effect,reduce the number of iterations,and reduce the smoothing of image at edge details.Simulation results show that the improved algorithm reduces the number of iterations retains the details of the image,well and the restored image has good visual effect.
引文
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[2]Cao W,Wang H B,Shi J,et al.Enhancement algorithm of finger vein image based on weighted guided filter with edge detection[J].Laser&Optoelectronics Progress,2017,54(2):021007.曹伟,王华彬,石军,等.基于边缘检测加权引导滤波的指静脉图像增强算法[J].激光与光电子学进展,2017,54(2):021007.
[3]Ni J Y,Li Q W,Zhou Y Q,et al.Underwater image restoration based on transmittance optimization and color temperature adjustment[J].Laser&Optoelectronics Progress,2017,54(1):011001.倪锦艳,李庆武,周亚琴,等.基于透射率优化和色温调节的水下图像复原[J].激光与光电子学进展,2017,54(1):011001.
[4]Tan Y Q,Zeng F J,Yue L,et al.An improved texture image synthesis algorithm[J].Laser&Optoelectronics Progress,2016,53(12):121001.谭永前,曾凡菊,岳莉,等.一种改进的纹理图像合成算法[J].激光与光电子学进展,2016,53(12):121001.
[5]Yin S B,Wang Y B,Li D P,et al.Fast blind restoration for microscopic visual defocused images based on two guided filterings[J].Acta Optica Sinica,2017,37(4):0410002.尹诗白,王一斌,李大鹏,等.两次引导滤波的显微视觉散焦图像快速盲复原[J].光学学报,2017,37(4):0410002.
[6]Barbu T.Anovel variational framework for structural image completion[C]∥International Conference on Optimization of Electrical and Electronic Equipment(OPTIM)&Intl Aegean Conference on Electrical Machines and Power Electronics(ACEMP),2017:815-820.
[7]Shen J H,Chan T F.Mathematical models for local nontexture inpaintings[J].SIAM Journal on Applied Mathematics,2002,62(3):1019-1043.
[8]Chan T F,Shen J H,Vese L.Variational PDEmodels in image processing[J].Notices of the American Mathematical Society,2003,50(1):14-26.
[9]Rudin L I,Osher S,Fatemi E.Nonlinear total variation based noise removal algorithms[J].Physica D:Nonlinear Phenomena,1992,60(1/2/3/4):259-268.
[10]Zhao Y W,Li X L.A rapid image inpainting algorithm based on TV model[J].Microelectronics&Computer,2009,26(6):253-256,260.赵颜伟,李象霖.一种基于TV模型的快速图像修复算法[J].微电子学与计算机,2009,26(6):253-256,260.
[11]Wang X H,Wang S,Fang L L.Image inpaiting based on TV model of direction gradient[J].Jilin Normal University Journal(Natural Science Edition),2012,33(2):1-7.王相海,王爽,方玲玲.图像修复的方向梯度TV模型研究[J].吉林师范大学学报(自然科学版),2012,33(2):1-7.
[12]Wang T,Wang J F,Bai Q,et al.Improved method of total variation image inpainting[J].Computer Systems&Applications,2013,22(3):121-124.王涛,王军锋,白青,等.改进的TV模型图像修复算法[J].计算机系统应用,2013,22(3):121-124.
[13]Cheng Q,Shen H F,Zhang L P,et al.Inpainting for remotely sensed images with a multichannel nonlocal total variation model[J].IEEE Transactions on Geoscience and Remote Sensing,2014,52(1):175-187.
[14]Liu H F,Xiong R Q,Ma S W,et al.Non-local extension of total variation regularization for image restoration[C]∥IEEE International Symposium on Circuits and Systems(ISCAS),2014:1102-1105.
[15]Duan J M,Pan Z K,Zhang B C,et al.Fast algorithm for color texture image inpainting using the non-local CTV model[J].Journal of Global Optimization,2015,62(4):853-876.
[16]Hou H N,Dai F,Yang C D.Image inpainting based on net function interpolation and TV model[J].Computer Systems&Applications,2016,25(12):117-125.侯海娜,戴芳,杨陈东.结合网函数插值与TV模型的图像修复算法[J].计算机系统应用,2016,25(12):117-125.
[17]Nair J J,Francis D.Robustnon-local total variation image inpainting[C]∥International Conference on Computational Intelligence and Communication Networks,2015:437-441.
[18]Zhang H Y,Peng Q C.An image inpainting algorithm based on p-Laplace operator[C]∥China Communications Society Communication Theory and Signal Processing Specialized Committee,2005Communication Theory and Signal Processing Annual Conference,2005.张红英,彭启琮.一种基于p-Laplace算子的图像修补方法[C]∥中国通信学会通信理论与信号处理专业委员会,2005年通信理论与信号处理年会,2005.