Abstract
This paper introduces a Bayesian restoration method for low-resolution images combined with a smoothness prior and a newly proposed adaptive bimodal prior. The bimodal prior is based on the fact that an edge pixel has a colour value that is typically a mixture of the colours of two connected regions, each having a dominant colour distribution. Local adaptation of the parameters of the bimodal prior is made to handle neighbourhoods which have typically more than two dominant colours. The maximum a posteriori estimator is worked out to solve the problem. Experimental results confirm the effectiveness of the proposed bimodal prior and show the visual superiority of our reconstruction scheme to other traditional interpolation and reconstruction methods for images with a strong colour modality like cartoons: noise and compression artefacts are removed very well and our method produces less blur and other annoying artefacts.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Allebach, J., Wong, P.W.: Edge-Directed Interpolation. In: Proc. of IEEE International Conference on Image Processing, pp. 707–710. IEEE Computer Society Press, Los Alamitos (1996)
Comaniciu, D., Meer, P.: Mean Shift: A Robust Approach Toward Feature Space Analysis. IEEE Trans. on Pattern Analysis and Machine Intelligence 24, 603–619 (2002)
Datsenko, D., Elad, M.: Example-Based Single Image Super-Resolution: A Global MAP Approach with Outlier Rejection. The Journal of Multidimensional Systems and Signal Processing (to appear)
Dempster, A.P., Lairde, N.M., Rubin, D.B.: Maximum Likelihood From Incomplete Data via the EM Algorithm. Journal of the Royal Statistical Society. Series B (Methodological) 39, 1–38 (1977)
Donaldson, K., Myers, G.: Bayesian Super-Resolution of Text in Video With a Text-Specific Bimodal Prior. International Journal on Document Analysis and Recognition 7, 159–167 (2005)
Farsiu, S., Robinson, M.D., Elad, M., Milanfar, P.: Fast and Robust Multiframe Super Resolution. IEEE Trans. on Image Processing 13, 1327–1344 (2004)
Freeman, W.T., Jones, T.R., Pasztor, E.C.: Example-Based Super-Resolution. IEEE Computer Graphics and Applications 22, 56–65 (2002)
Honda, H., Haseyama, M., Kitajima, H.: Fractal Interpolation For Natural Images. In: Proc. of IEEE International Conference of Image Processing, vol. 3, pp. 657–661. IEEE Computer Society Press, Los Alamitos (1999)
Ledda, A., Luong, H.Q., Philips, W., De Witte, V., Kerre, E.E.: Image Interpolation Using Mathematical Morphology. In: Proc. of 2nd IEEE International Conference On Document Image Analysis For Libraries, IEEE Computer Society Press, Los Alamitos (to appear) (2006)
Lehmann, T., Gönner, C., Spitzer, K.: Survey: Interpolations Methods In Medical Image Processing. IEEE Trans. on Medical Imaging 18, 1049–1075 (1999)
Li, X., Orchard, M.T.: New Edge-Directed Interpolation. IEEE Trans. on Image Processing 10, 1521–1527 (2001)
Luong, H.Q., De Smet, P., Philips, W.: Image Interpolation Using Constrained Adaptive Contrast Enhancement Techniques. In: Proc. of IEEE International Conference of Image Processing, vol. 2, pp. 998–1001. IEEE Computer Society Press, Los Alamitos (2005)
Luong, H.Q., Ledda, A., Philips, W.: An Image Interpolation Scheme for Repetitive Structures. In: Campilho, A., Kamel, M. (eds.) ICIAR 2006. LNCS, vol. 4141, pp. 104–115. Springer, Heidelberg (2006)
Matas, J., Koubaroulis, D., Kittler, J.: Colour Image Retrieval and Object Recognition Using the Multimodal Neighbourhood Signature. In: Vernon, D. (ed.) ECCV 2000. LNCS, vol. 1842, pp. 48–64. Springer, Heidelberg (2000)
Meijering, E.H.W., Niessen, W.J., Viergever, M.A.: Quantitative Evaluation Of Convolution-Based Methods For Medical Image Interpolation. Medical Image Analysis 5, 111–126 (2001)
Morse, B.S., Schwartzwald, D.: Isophote-Based Interpolation. In: Proc. of IEEE International Conference on Image Processing, pp. 227–231. IEEE Computer Society Press, Los Alamitos (1998)
Muresan, D.: Fast Edge Directed Polynomial Interpolation. In: Proc. of IEEE International Conference of Image Processing, vol. 2, pp. 990–993 (2005)
Pižurica, A., Vanhamel, I., Sahli, H., Philips, W., Katartzis, A.: A Bayesian Approach To Nonlinear Diffusion Based On A Laplacian Prior For Ideal Image Gradient. In: Proc. of IEEE Workshop On Statistical Signal Processing, IEEE Computer Society Press, Los Alamitos (2005)
Thouin, P., Chang, C.: A Method For Restoration of Low-Resolution Document Images. International Journal on Document Analysis and Recognition 2, 200–210 (2000)
Tschumperlé, D.: Fast Anisotropic Smoothing of Multi-Valued Images using Curvature-Preserving PDE’s. International Journal of Computer Vision 1, 65–82 (2006)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Luong, H., Philips, W. (2007). Reconstruction of Low-Resolution Images Using Adaptive Bimodal Priors. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2007. Lecture Notes in Computer Science, vol 4633. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74260-9_7
Download citation
DOI: https://doi.org/10.1007/978-3-540-74260-9_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74258-6
Online ISBN: 978-3-540-74260-9
eBook Packages: Computer ScienceComputer Science (R0)