Missing Texture Reconstruction Method Based on Error Reduction Algorithm Using Fourier Transform Magnitude Estimation Scheme

A missing texture reconstruction method based on an error reduction (ER) algorithm, including a novel estimation scheme of Fourier transform magnitudes is presented in this brief. In our method, Fourier transform magnitude is estimated for a target patch including missing areas, and the missing intensities are estimated by retrieving its phase based on the ER algorithm. Specifically, by monitoring errors converged in the ER algorithm, known patches whose Fourier transform magnitudes are similar to that of the target patch are selected from the target image. In the second approach, the Fourier transform magnitude of the target patch is estimated from those of the selected known patches and their corresponding errors. Consequently, by using the ER algorithm, we can estimate both the Fourier transform magnitudes and phases to reconstruct the missing areas.

[1]  Guillermo Sapiro,et al.  Simultaneous structure and texture image inpainting , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[2]  Daniel Cohen-Or,et al.  Fragment-based image completion , 2003, ACM Trans. Graph..

[3]  J. Gower.  Adding a point to vector diagrams in multivariate analysis , 1968 .

[4]  Miki Haseyama,et al.  POCS-Based Texture Reconstruction Method Using Clustering Scheme by Kernel PCA , 2007, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

[5]  Michael Elad,et al.  Sparse Representation for Color Image Restoration , 2008, IEEE Transactions on Image Processing.

[6]  Sung Yong Shin,et al.  On pixel-based texture synthesis by non-parametric sampling , 2006, Comput. Graph..

[7]  I. B. Fidaner.  A Survey on Variational Image Inpainting , Texture Synthesis and Image Completion , 2007 .

[8]  Toshiyuki Amano,et al.  Image interpolation using BPLP method on the eigenspace , 2007, Systems and Computers in Japan.

[9]  Zongben Xu,et al.  Image Inpainting by Patch Propagation Using Patch Sparsity , 2010, IEEE Transactions on Image Processing.

[10]  Charlie C. L. Wang,et al.  Interactive Image Inpainting Using DCT Based Exemplar Matching , 2009, ISVC.

[11]  J R Fienup,et al.  Phase retrieval algorithms: a comparison. , 1982, Applied optics.

[12]  Sayali Baheti,et al.  Region Filling and Object Removal by Exemplar based Image Inpainting , 2015 .

[13]  Charlie C. L. Wang,et al.  Fast Query for Exemplar-Based Image Completion , 2010, IEEE Transactions on Image Processing.

[14]  Guillermo Sapiro,et al.  Structure and texture filling-in of missing image blocks in wireless transmission and compression applications , 2003, IEEE Trans. Image Process..

[15]  P. Sengottuvelan,et al.  Combined Structure and Texture Image Inpainting Algorithm for Natural Scene Image Completion , 2011 .

[16]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[17]  Patrick Pérez,et al.  Region filling and object removal by exemplar-based image inpainting , 2004, IEEE Transactions on Image Processing.

[18]  Guillermo Sapiro,et al.  Filling-in by joint interpolation of vector fields and gray levels , 2001, IEEE Trans. Image Process..