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Matrix decomposition graphics processing unit solver for Poisson image editing

[+] Author Affiliations
Zhao Lei

Zhejiang University, Department of Computer Science and Technology, Room 208, East Caoguangbiao Building, No. 38, Zheda Road, Hangzhou, Zhejiang 310027, China

Li Wei

Zhejiang University, Department of Computer Science and Technology, Room 208, East Caoguangbiao Building, No. 38, Zheda Road, Hangzhou, Zhejiang 310027, China

J. Electron. Imaging. 21(4), 043007 (Oct 05, 2012). doi:10.1117/1.JEI.21.4.043007
History: Received May 19, 2012; Revised July 20, 2012; Accepted September 13, 2012
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Abstract.  In recent years, gradient-domain methods have been widely discussed in the image processing field, including seamless cloning and image stitching. These algorithms are commonly carried out by solving a large sparse linear system: the Poisson equation. However, solving the Poisson equation is a computational and memory intensive task which makes it not suitable for real-time image editing. A new matrix decomposition graphics processing unit (GPU) solver (MDGS) is proposed to settle the problem. A matrix decomposition method is used to distribute the work among GPU threads, so that MDGS will take full advantage of the computing power of current GPUs. Additionally, MDGS is a hybrid solver (combines both the direct and iterative techniques) and has two-level architecture. These enable MDGS to generate identical solutions with those of the common Poisson methods and achieve high convergence rate in most cases. This approach is advantageous in terms of parallelizability, enabling real-time image processing, low memory-taken and extensive applications.

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Citation

Zhao Lei and Li Wei
"Matrix decomposition graphics processing unit solver for Poisson image editing", J. Electron. Imaging. 21(4), 043007 (Oct 05, 2012). ; http://dx.doi.org/10.1117/1.JEI.21.4.043007


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