Abstract
Image completion is a method to fill the missing portions of an image caused by the removal of one or more foreground or background elements. In this paper a novel image completion algorithm is proposed for removing significant objects from natural images or photographs. The completion is realized in the following three steps. First, a gradient-based model is presented to determine the gradient-patch filling order. This step is critical because a better filling order can improve the continuation of image structures. Second, we implement the gradient-patch update strategy by measuring the exponential distance between the source patch and the target one in gradient domain. In order to find a better patch matching and propagating algorithm, we incorporate the gradient and color information together to determine the target patch. Third, a complete image is achieved by solving the Poisson equation with the updated image gradient map. Some experimental results on real-scene photographs are given to demonstrate both the efficiency and image equality of our novel method.
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Shen, J., Jin, X., Zhou, C. (2005). Gradient Based Image Completion by Solving Poisson Equation. In: Ho, YS., Kim, H.J. (eds) Advances in Multimedia Information Processing - PCM 2005. PCM 2005. Lecture Notes in Computer Science, vol 3767. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11581772_23
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DOI: https://doi.org/10.1007/11581772_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30027-4
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