Constrained texture synthesis via energy minimization
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Published on: January 19, 2016
Ganesh Ramanarayanan1, Kavita Bala
1Department of Computer Science, Cornell University, Ithaca, NY 14853, USA. graman@cs.cornell.edu
Abstract:
This paper describes CMS (constrained minimization synthesis), a fast, robust texture synthesis algorithm that creates output textures while satisfying constraints. We show that constrained texture synthesis can be posed in a principled way as an energy minimization problem that requires balancing two measures of quality: constraint satisfaction and texture seamlessness. We then present an efficient algorithm for finding good solutions to this problem using an adaptation of graphcut energy minimization. CMS is particularly well suited to detail synthesis, the process of adding high-resolution detail to low-resolution images. It also supports the full Image Analogies framework, while providing superior image quality and performance. CMS is easily extended to handle multiple constraints on a single output, thus enabling novel applications that combine both user-specified and image-based control.
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