出版社：The Institute of Image Information and Television Engineers
摘要：We present a variational motion de-blurring method that minimizes the regularized energy functional defined with a spatially variant model of motion blurs. Unlike spatially invariant image blurs, minimization cannot be achieved in a closed non-iterative way, and we therefore need to derive its iterative algorithm. The standard regularization method uses a square function to measure the energy of its solution function, and utilizes the energy functional composed of the data-fidelity energy term to measure deviation of the solution function from the assumed model of motion blurs and the regularization energy term to impose smoothness constraints on the solution function. However, the standard regularization method is not necessarily appropriate for motion de-blurring, because it is sensitive to model errors and errors are inevitable in motion estimation. To improve robustness against model errors, we introduced a robust estimation function into the data-fidelity energy term.
