Image Inpainting Technology Based on Total Generalized Variation Regularization

doi:10.3969/j.issn.1006-2475.2020.07.022

Abstract

Abstract: Image inpainting is a hot spot in digital image processing and computer graphics. To better recover the image, a new image inpainting model based on total generalized variation is proposed. Then, the first order primal dual method is employed to solve the proposed model. The experiments are carried out to verify the presented scheme based on the value of similarity index and the peak signal to noise ratio. The experimental results show that the proposed scheme is capable of achieving good image recovery quality.

Key words: total generalized variation, total variation, first order primal dual method, image inpainting

CLC Number:

TP751.1

CHEN Ying-pin, KE Su-ling, HUANG Hui-ying, WU Ri-sheng, WANG Ling-zhi. Image Inpainting Technology Based on Total Generalized Variation Regularization[J]. Computer and Modernization, 2020, 0(07): 117-120.

References ［23］

［1］	魏欣,蒋华伟. 基于纹理和结构的图像修复算法研究［J］. 计算机技术与发展, 2010,20(9):90-93.
［2］	徐书方. 图像去噪偏微分方程综合模型的研究［D］. 大连：大连理工大学, 2010.
［3］	廉晓丽,徐中宇,冯丽丽，等. 一种新的基于偏微分方程的图像修复［J］. 计算机工程, 2009,35（6）:234-236.
［4］	CRIMINISI A, PEREZ P, TOYAMA K. Region filling and object removal by exemplar-based image inpainting［J］. IEEE Transactions on Image Processing, 2004,13(9):1200-1212.
［5］	CHEN Y P, PENG Z M, LI M H, et al. Seismic signal denoising using total generalized variation with overlapping group sparsity in the accelerated ADMM framework［J］. Journal of Geophysics and Engineering, 2019,16(1):30-51.
［6］	彭真明,陈颖频,蒲恬,等. 基于稀疏表示及正则约束的图像去噪方法综述［J］. 数据采集与处理, 2018,33(1):1-11.
［7］	肖亮. 基于变分PDE和多重分形的图像建模理论、算法与应用［D］. 南京：南京理工大学, 2003.
［8］	孙向荣,刘芳芳. 图像修复TV模型的快速算法研究［J］. 计算机技术与发展, 2014,21(11):144-147.
［9］	LIU X G, CHEN Y P, PENG Z M, et al. Infrared image super-resolution reconstruction based on quaternion fractional order total variation with Lp quasinorm［J］. Applied Sciences, 2018,8(10): Article No.1864, DOI: 10.3390/app8101864.
［10］	ZHAO Y Q, JI D J, CHEN Y P, et al. A new in-line X-ray phase-contrast computed tomography reconstruction algorithm based on adaptive-weighted anisotropic TpV regularization for insufficient data［J］. Journal of Synchrotron Radiation, 2019,26(4):1330-1342.
［11］	林凡,程祝媛,陈颖频,等. 基于交叠组合稀疏全变分的图像去噪方法［J］. 科学技术与工程, 2018(18):67-73.
［12］	KNOLL F, BREDIES K, POCK T, et al. Second order total generalized variation (TGV) for MRI［J］. Magnetic Resonance in Medicine, 2011,65(2):480-491.
［13］	BREDIES K, HOLLER M. Regularization of linear inverse problems with total generalized variation［J］. Journal of Inverse and Ill-Posed Problems, 2014,22(6):871-913.
［14］	BREDIES K, KUNISCH K, POCK T. Total generalized variation［J］. SIAM Journal on Imaging Sciences, 2010,3(3):492-526.
［15］	KNOLL F, SCHULTZ G, BREDIES K, et al. Reconstruction of undersampled radial PatLoc imaging using total generalized variation［J］. Magnetic Resonance in Medicine, 2013,70(1):40-52.
［16］	KONG D H, PENG Z M. Seismic random noise attenuation using shearlet and total generalized variation［J］. Journal of Geophysics and Engineering, 2015,12(6):1024-1035.
［17］	LIU X G, CHEN Y P, PENG Z M, et al. Total variation with overlapping group sparsity and Lp quasinorm for infrared image deblurring under salt-and-pepper noise［J］. Journal of Electronic Imaging, 2019,28(4):043031.
［18］	NIU S, GAO Y, BIAN Z, et al. Sparse-view x-ray CT reconstruction via total generalized variation regularization［J］. Physics in Medicine and Biology, 2014,59(12):2997-3017.
［19］	董卫东,彭宏京. 基于紧框架的二阶总广义变分图像修复模型［J］. 计算机工程与应用, 2018,54(11):178-184.
［20］	CHAMBOLLE A, POCK T. A first-order primal-dual algorithm for convex problems with applications to imaging［J］. Journal of Mathematical Imaging and Vision, 2011,40(1):120-145.
［21］	DU Y, CHEN Y P, MENG G Y, et al. Fault severity monitoring of rolling bearings based on texture feature extraction of sparse time-frequency images［J］. Applied Sciences, 2018,8(9): Article No.1538, DOI: 10.3390/app8091538.
［22］	WANG Z, BOVIK A C, SHEIKH H R, et al. Image quality assessment: From error visibility to structural similarity［J］. IEEE Transactions on Image Processing, 2004,13(4):600-612.
［23］	LI S, HE Y M, CHEN Y P, et al. Fast multi-trace impedance inversion using anisotropic total p-variation regularization in the frequency domain［J］. Journal of Geophysics and Engineering, 2018,15(5):2171-2182.

[1]	ZHAN Wei， ZHANG Ke， XU Huan， LUO Xian， LONG Fei, JI Yi-yi. A Mobile Face Recognition Technology Based on Diffusion Speed [J]. Computer and Modernization, 2019, 0(03): 28-.
[2]	LIU Ya-nan, PENG Ren-yong, WANG Lin. Super-resolution Image Reconstruction Based on Adaptive Fractional Order Total Variation Regularization [J]. Computer and Modernization, 2018, 0(09): 56-.