Image inpainting based on sparse representations with a perceptual metric

被引：0
作者：
Takahiro Ogawa
Miki Haseyama
机构：
[1] Hokkaido University,Graduate School of Information Science and Technology
来源：
EURASIP Journal on Advances in Signal Processing | / 2013卷
关键词：
Mean Square Error; Sparse Representation; Optimal Vector; Target Image; Image Inpainting;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper presents an image inpainting method based on sparse representations optimized with respect to a perceptual metric. In the proposed method, the structural similarity (SSIM) index is utilized as a criterion to optimize the representation performance of image data. Specifically, the proposed method enables the formulation of two important procedures in the sparse representation problem, 'estimation of sparse representation coefficients’ and 'update of the dictionary’, based on the SSIM index. Then, using the generated dictionary, approximation of target patches including missing areas via the SSIM-based sparse representation becomes feasible. Consequently, image inpainting for which procedures are totally derived from the SSIM index is realized. Experimental results show that the proposed method enables successful inpainting of missing areas.
引用
收藏
相关论文
共 143 条
[1]  
Yan R(2013)Nonlocal hierarchical dictionary learning using wavelets for image denoising IEEE Trans. Image Process 22 4689-4698
[2]  
Shao L(2005)A review of image denoising algorithms, with a new one Multiscale Model. Simul 4 490-530
[3]  
Liu Y(2008)An overview and performance evaluation of classification-based least squares trained filters IEEE Trans. Image Process 17 1772-1782
[4]  
Buades A(2007)Review and preview: disocclusion by inpainting for image-based rendering IEEE Trans. Syst., Man, Cybern., Part, C: Appl. Rev 37 527-540
[5]  
Coll B(1998)Level lines based disocclusion Proc. IEEE Int. Conf. Image Process. (ICIP) 3 259-263
[6]  
Morel J(2001)Navier-stokes, fluid dynamics, and image and video inpainting Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit 1 355-362
[7]  
Shao L(2001)Nontexture inpainting by curvature-driven diffusions J. Vis. Commun. Image Representation 12 436-449
[8]  
Zhang H(2005)Restoration method of missing areas in still images using GMRF model IEEE Int. Symp. Circuits Syst. (ISCAS) 5 4931-4934
[9]  
de Haan G(2005)Edge-based image restoration IEEE Trans. Image Process 14 1454-1468
[10]  
Tauber Z(2006)A global approach for solving evolutive heat transfer for image denoising and inpainting IEEE Trans. Image Process 15 2558-2574
12345678910