Abstract
For images with partial blur such as local defocus or local motion, deconvolution with just a single point spread function surely could not restore the images correctly. Thus, restoration relying on blur region segmentation is developed widely. In this paper, we propose an automatic approach for blur region extraction. Firstly, the image is divided into patches. Then, the patches are marked by three blur features: gradient histogram span, local mean square error map, and maximum saturation. The combination of three measures is employed as the initialization of iterative image matting algorithm. At last, we separate the blurred and non-blurred region through the binarization of alpha matting map. Experiments with a set of natural images prove the advantage of our algorithm.
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References
Gonzalez, C., Woods, E.: Digital Image Processing, 2nd edn. Electronic Industry Press, Beijing (2002)
Zou, Y.: Deconvolution and Signal Recovery. National defence industry press, Beijing (2001)
Xu, T., Gondra, I.: A simple and effective texture characterization for image segmentation. Signal Image Video Process. 6(2), 231–245 (2010)
Freedman, D.: An improved image graph for semi-automatic segmentation. Signal Image Video Process. (2010). doi:10.1007/s11760-010-0181-9
Trussell, H., Hunt, B.: Image restoration of space variant blurs by sectioned methods. IEEE International Conference on Acoustics, Speech, and Signal Processing, Apr. 10–12, pp. 196–198 (1978)
Trussell, H., Hunt, B.: Sectioned methods for image restoration. IEEE Trans. Acoust. Speech Signal Process. 26(2), 157–164 (1978)
Costello, T., Mikhael, W.: Efficient restoration of space-variant blurs from physical optics by sectioning with modified Wiener filtering. Digit. Signal Process. 13(1), 1–22 (2003)
Lin, H., Li, K., Chang, H.: Vehicle speed detection from a single motion blurred image. Image Vis. Comput. 26(10), 1327–1337 (2008)
Marziliano, P., Dufaux, F., Winkler, S., Ebrahimi, T.: A no-reference perceptual blur metric. Proc. International Conference on Image Processing, Jun. 24–28, pp. 57–60 (2002)
Rugna, J., Konik, H.: Automatic blur detection for metadata extraction in content-based retrieval context. Proc. SPIE 5304, 285–294 (2003)
Bar, L., Sochen, N., Kiryati, N.: Restoration of images with piecewise space-variant blur. Scale Space Var. Methods Comput. Vis. 4485, 533–544 (2007)
Freeman, W., Adelson, E.: The design and use of steerable filters. IEEE Trans. Pattern Anal. Mach. Intell. 13(9), 891–906 (1991)
Zhang, W., Bergholm, F.: Multi-Scale Blur estimation and edge type classification for scene analysis. Int. J. Comput. Vis. 24(3), 219–250 (1997)
Chung, Y., Wang, J., Bailey, R., Chen, S., Chang, S.: A nonparametric blur measure based on edge analysis for image processing applications. IEEE Conference on Cybernetics and Intelligent Systems, Dec. 1–3, pp. 356–360 (2004)
Liu, R., Li, Z., Jia, J.: Image partial blur detection and classification. IEEE Conference on Computer Vision and Pattern Recognition, Anchorage, Alaska, USA, Jun. 23–28, pp. 954–961 (2008)
Wang, J., Cohen, M.: An iterative optimization approach for unified image segmentation and matting. Proceedings of tenth International Computer Vision, Oct. 17–21, pp. 936–943 (2005)
Levin, A., Lischinski, D., Weiss, Y.: A closed form solution to natural image matting. IEEE Trans. Pattern Anal. Mach. Intell. 30(2), 228–242 (2008)
Levin, A., Acha, A., Lischinski, D.: Spectral matting. IEEE Conference on Computer Vision and Pattern Recognition, Jun. 17–22, pp. 1–8 (2007)
Li, Y., Sun, J., Tang, C., Shum, H.: Lazy snapping. ACM Trans. Graph. 23(3), 303–308 (2004)
Rother, C., Kolmogorov, V., Blake, A.: Grab cut: interactive foreground extraction using iterated graph cuts. ACM Trans. Graph. 23(3), 309–314 (2005)
Roth, S., Black, M.: Fields of experts: A framework for learning image priors. IEEE Conference on Computer Vision and Pattern Recognition, Jun. 20–25, pp. 860–867 (2005)
Levin, A.: Blind motion deblurring using image statistics. Adv. Neural Inf. Process. Syst. 19, 841–848 (2007)
Fergus, R., Singh, B., Hertzmann, A., Roweis, S.T., Freeman, W.T.: Removing camera shake from a single photograph. ACM Trans. Graph. 25(3), 787–794 (2006)
Oliveira, M., Bowen, B., Mckenna, R., Chang, Y.: Fast digital image inpainting. Proceedings International Conference on Visualization, Imaging and Image Processing (VIIP 2001): Marbella, Spain, pp. 261–266, (2001)
Acknowledgments
We wish to thank the reviewers for their comments and suggestions which have helped improve the content of the paper. And we thank Dr. Li for checking the text. This research is supported by the National Basic Research Program (973) of China (Grant No. 2009CB724006) and the National Hi-Tech Research and Development Program (863) of China (2009AA12Z108).
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Zhao, J., Feng, H., Xu, Z. et al. Automatic blur region segmentation approach using image matting. SIViP 7, 1173–1181 (2013). https://doi.org/10.1007/s11760-012-0381-6
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DOI: https://doi.org/10.1007/s11760-012-0381-6