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24 June 2005 Model-based PDE method and model-free PDE method for motion de-blurring
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Proceedings Volume 5960, Visual Communications and Image Processing 2005; 59605A (2005)
Event: Visual Communications and Image Processing 2005, 2005, Beijing, China
Once image motion is accurately estimated, we can utilize those motion estimates for image sharpening and we can remove motion blurs. First, for the motion de-blurring, this paper presents a model-based PDE method that minimizes the regularized energy functional defined with a spatially variant model of motion blurs. Unlike the case of spatially invariant image blurs, the minimization of the energy functional cannot be achieved in a closed non-iterative way, and we derive its iterative algorithm. The standard regularization method uses a square function to measure energy of its solution function, and employs the energy functional composed of the data-fidelity energy term to measure a deviation of a solution function from the assumed model of motion blurs and the regularization energy term to impose smoothness constraints on a solution function. However, the standard variational method is not proper for the motion de-blurring, because it is sensitive to model errors, and occurrence of errors are inevitable in motion estimation. To improve the robustness against the model errors, we employ a nonlinear robust estimation function for measuring energy to be minimized. Secondly, this paper experimentally compares the model-based PDE method with our previously presented model-free PDE method that does not need any accurate blur model. In the model-error-free case the model-based PDE method outperforms the model-free PDE method, whereas in the model-error case the latter works better than the former.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Takahiro Saito, Hiroyuki Harada, and Takashi Komatsu "Model-based PDE method and model-free PDE method for motion de-blurring", Proc. SPIE 5960, Visual Communications and Image Processing 2005, 59605A (24 June 2005);

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