文件名称：Variational Approach to Super-resolution with Nonlocal TV Regularization Term
文件大小：559KB
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更新时间：2016-11-16 16:45:04
超分辨率重建 变分方法
Multi frame super resolution SR reconstruction algorithms make use of complimentary information among low resolution LR images to yield a high resolution HR image Inspired by recent development on the video denosing problem we propose a robust variational approach for SR based on a constrained variational model that use the nonlocal total variation TV as a regularization term In our method a weighted fidelity term is proposed to take into account inaccurate estimates of the registration parameters and the point spread function Moreover we introduce the nonlocal TV as a regularization term in order to take into account complex spatial interactions within images In this way important features and fine details are enhanced simultaneously with noise reduction Furthermore an alternative nonlocal TV regularization is proposed based on a better weight function which integrates gradient similarity and radiometric similarity Experiments show the effectiveness and practicability of the proposed method ">Multi frame super resolution SR reconstruction algorithms make use of complimentary information among low resolution LR images to yield a high resolution HR image Inspired by recent development on the video denosing problem we propose a robust variational approach for SR based on a constrain [更多]