Abstract
This paper presents a novel, automated method to remove partial occlusion from a single image. In particular, we are concerned with occlusions resulting from objects that fall on or near the lens during exposure. For each such foreground object, we segment the completely occluded region using a geometric flow. We then look outward from the region of complete occlusion at the segmentation boundary to estimate the width of the partially occluded region. Once the area of complete occlusion and width of the partially occluded region are known, the contribution of the foreground object can be removed. We present experimental results which demonstrate the ability of this method to remove partial occlusion with minimal user interaction. The result is an image with improved visibility in partially occluded regions, which may convey important information or simply improve the image’s aesthetics.
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References
Chuang, Y., Curless, B., Salesin, D.H., Szeliski, R.: A Bayesian Approach to Digital Matting. In: CVPR 2001, pp. 264–271 (2001)
Debevec, P., Malik, J.: Recovering High Dynamic Range Radiance Maps from Photographs. In: SIGGRAPH 1997, pp. 369–378 (1997)
Favaro, P., Soatto, S.: Seeing Beyond Occlusions (and other marvels of a finite lens aperture). In: CVPR 2003, pp. 579–586 (2003)
Grayson, M.: The Heat Equation Shrinks Embedded Plane Curves to Round Points. Journal of Differential Geometry 26, 285–314 (1987)
Levoy, M., Chen, B., Vaish, V., Horowitz, M., McDowall, I., Bolas, M.: Synthetic Aperture Confocal Imaging. In: SIGGRAPH 2004, pp. 825–834 (2004)
Perona, P., Malik, J.: Scale-Space and Edge Detection using Anisotropic Diffusion. IEEE Trans. on Patt. Anal. and Mach. Intell. 12(7), 629–639 (1990)
McCloskey, S., Langer, M., Siddiqi, K.: Seeing Around Occluding Objects. In: Proc. of the Int. Conf. on Patt. Recog. vol. 1, pp. 963–966 (2006)
McGuire, M., Matusik, W., Pfister, H., Hughes, J.F., Durand, F.: Defocus Video Matting. ACM Trans. Graph. 24(3) (2005)
Reinhard, E., Khan, E.A.: Depth-of-field-based Alpha-matte Extraction. In: Proc. 2nd Symp. on Applied Perception in Graphics and Visualization 2005, pp. 95–102 (2005)
Sethian, J.A.: Level Set Methods and Fast Marching Methods. Cambridge University Press, Cambridge (1999)
Sun, J., Jia, J., Tang, C., Shum, H.: Poisson Matting. ACM Trans. Graph. 23(3) (2004)
Tamaki, T., Suzuki, H.: String-like Occluding Region Extraction for Background Restoration. In: Proc. of the Int. Conf. on Patt. Recog. vol. 3, pp. 615–618 (2006)
Vasilevskiy, A., Siddiqi, K.: Flux Maximizing Geometric Flows. IEEE Trans. on Patt. Anal. and Mach. Intell. 24(12), 1565–1578 (2002)
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McCloskey, S., Langer, M., Siddiqi, K. (2007). Automated Removal of Partial Occlusion Blur. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds) Computer Vision – ACCV 2007. ACCV 2007. Lecture Notes in Computer Science, vol 4843. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76386-4_25
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DOI: https://doi.org/10.1007/978-3-540-76386-4_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76385-7
Online ISBN: 978-3-540-76386-4
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