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A unified approach to superresolution and multichannel blind deconvolution

机译:超分辨率和多通道盲反卷积的统一方法

摘要

This paper presents a new approach to the blind deconvolution and superresolution problem of multiple degraded low-resolution frames of the original scene. We do not assume any prior information about the shape of degradation blurs. The proposed approach consists of building a regularized energy function and minimizing it with respect to the original image and blurs, where regularization is carried out in both the image and blur domains. The image regularization based on variational principles maintains stable performance under severe noise corruption. The blur regularization guarantees consistency of the solution by exploiting differences among the acquired low-resolution images. Several experiments on synthetic and real data illustrate the robustness and utilization of the proposed technique in real applications. © 2007 IEEE.
机译:本文提出了一种新的方法来解决原始场景中多个降级的低分辨率帧的盲反卷积和超分辨率问题。我们不假定有关降级模糊形状的任何先验信息。所提出的方法包括建立一个正规化的能量函数,并相对于原始图像和模糊化将其最小化,其中在图像域和模糊域中均进行正规化。基于变分原理的图像正则化可在严重噪声破坏下保持稳定的性能。模糊正则化通过利用所获取的低分辨率图像之间的差异来保证解决方案的一致性。在合成和真实数据上的一些实验说明了该技术在实际应用中的鲁棒性和利用率。 ©2007 IEEE。

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