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从非均匀测量中提取基本高分辨率图像融合。

Frame fundamental high-resolution image fusion from inhomogeneous measurements.

机构信息

Department of Mathematics, San Francisco State Univeristy, San Francisco, CA 94132, USA.

出版信息

IEEE Trans Image Process. 2012 Sep;21(9):4002-15. doi: 10.1109/TIP.2012.2201489. Epub 2012 May 25.

Abstract

Frame and fusion frame high-resolution image fusion formulations are presented. These techniques use the physical point spread function (PSF) of cameras as the building block of the mathematical frames in the fusion process. Cameras producing the low-resolution images are allowed to be different, and thereby possess different PSFs. Fused image reconstructions are carried out by a dimension invariance principle and by a set of iterative reconstruction algorithms. These frame fundamental approaches are also seen to be robust to realistic fusion problems from inhomogeneous image measurements (taken at different space or time or by different cameras), which is one of the main focuses of this paper. The effectiveness of this approach is demonstrated through both simulated and realistic examples. The results are quite encouraging.

摘要

提出了帧和融合框架高分辨率图像融合公式。这些技术使用相机的物理点扩散函数 (PSF) 作为融合过程中数学帧的构建块。允许使用产生低分辨率图像的相机不同,从而具有不同的 PSF。通过维度不变性原理和一组迭代重建算法进行融合图像重建。这些帧基本方法也被证明对来自不均匀图像测量(在不同的空间或时间或不同的相机拍摄)的现实融合问题具有鲁棒性,这是本文的主要重点之一。通过模拟和实际示例证明了这种方法的有效性。结果非常令人鼓舞。

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