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Abstract: We present an algorithm for image compression based on an image inpainting method. First the image regions that can be accurately recovered are located. Then, to reduce the data, information of such regions is removed. The remaining data besides essential details for recovering the removed regions are encoded to produce output data. At the decoder, an inpainting method is applied to retrieve removed regions using information extracted at the encoder. The image inpainting technique utilizes partial differential equations (PDEs) for recovering information. It is designed to achieve high performance in terms of image compression criteria. This algorithm was examined for various images. A high compression ratio of 1:40 was achieved at an acceptable quality. Experimental results showed attainable visible quality improvement at a high compression ratio compared with JPEG.

[1] Bertalmio, M., 2006. Strong-continuation, contrast-invariant inpainting with a third-order optimal PDE. IEEE Trans. Image Process., 15(7):1934-1938.

[2] Bertalmio, M., Sapiro, G., Caselles, V., Ballester, C., 2000. Image Inpainting. Proc. Int. Conf. on Computer Graphics and Interactive Techniques, p.417-424.

[3] Bertalmio, M., Bertozzi, A.L., Sapiro, G., 2001. Navier-Stokes, Fluid Dynamics, and Image and Video Inpainting. Proc. IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, 1:355-362.

[4] Briggs, W.L., Henson, V.E., McCormick, S.F., 2000. A Multi-Grid Tutorial (2nd Ed.). Society for Industrial and Applied Mathematics (SIAM), Philadelphia, p.1-85.

[5] Chan, T.F., Shen, J., 2005a. Image Processing and Analysis. Society for Industrial and Applied Mathematics (SIAM), Philadelphia, p.277-279.

[6] Chan, T.F., Shen, J., 2005b. Variational image inpainting. Commun. Pure Appl. Math., 58(5):579-619.

[7] Criminisi, A., Perez, P., Toyama, K., 2004. Region filling and object removal by exemplar-based image inpainting. IEEE Trans. Image Process., 13(9):1200-1212.

[8] Galić, I., Weickert, J., Welk, M., Bruhn, A., Belyaey, A., 2008. Image compression with anisotropic diffusion. J. Math. Imag. Vis., 31(2-3):255-269.

[9] Grossauer, H., 2004. A combined PDE and texture synthesis approach to inpainting. LNCS, 3022:214-224.

[10] Höntsch, I., Karam, L.J., 2000. Locally adaptive perceptual image coding. IEEE Trans. Image Process., 9(9):1472-1483.

[11] Liu, D., Sun, X.Y., Wu, F., Li, S.P., Zhang, Y.Q., 2007. Image compression with edge-based inpainting. IEEE Trans. Circ. Syst. Video Technol., 17(10):1273-1287.

[12] Malo, J., Epifanio, I., Navarro, R., Simoncelli, E.P., 2006. Nonlinear image representation for efficient perceptual coding. IEEE Tran. Image Process., 15(1):68-80.

[13] Patwardhan, K.A., Sapiro, G., Bertalmio, M., 2005. Video Inpainting of Occluding and Occluded Objects. IEEE Int. Conf. on Image Processing, 2:69-72.

[14] Pennebaker, W.B., Mitchell, J.L., 1992. JPEG: Still Image Data Compression Standard. Kluwer Academic Publishers, Norwell, MA, USA.

[15] Perona, P., Malik, J., 1990. Scale-space and edge detection using anisotropic diffusion. IEEE Trans. Pattern Anal. Mach. Intell., 12(7):629-639.

[16] Rane, S.D., Sapiro, G., Bertalmio, M., 2003. Structure and texture filling-in of missing image blocks in wireless transmission and compression applications. IEEE Trans. Image Process., 12(3):296-303.

[17] Shen, J., Chan, T.F., 2002. Mathematical models for local nontexture inpaintings. SIAM J. Appl. Math, 62(3):1019-1043.

[18] Tai, X.C., Osher, S., Holm, R., 2006. Image Inpainting Using a TV-Stokes Equation. Image Processing Based on Partial Differential Equations, p.3-22.

[19] Taubman, D.S., Marcellin, M.W., 2002. JPEG 2000: Image Compression Fundamentals, Standards and Practice. Kluwer Academic Publishers, Norwell, MA, USA.

[20] Wang, Z., Bovik, A.C., 2009. Mean squared error: love it or leave it? A new look at signal fidelity measures. IEEE Signal Process. Mag., 26(1):98-117.

[21] Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P., 2004. Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process., 13(4):600-612.