Regularization in Super-resolution Reconstruction of Biomedical Images using Gradient Vector Field

机译：使用梯度矢量字段的超分辨率重构正规化

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The paper presents a method for regularization parameter in super-resolution reconstruction of biomedical images using the gradient vector field of a preliminary high resolution image. This works well in suppressing artifacts and excessive smoothing compared with Tikhonov regularization. Experiments of synthetic and real MRI images are presented to verify the performance of reconstruction.

机译：本文介绍了使用初步高分辨率图像的梯度矢量字段的生物医学图像超分辨率重构中的正则化参数的方法。与Tikhonov规则化相比，这适用于抑制伪影和过度平滑。介绍了合成和实际MRI图像的实验，以验证重建的性能。

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《International Special Topic Conference on Information Technology and Applications in Biomedicine》|2008年||共3页
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Xin Zhang; Edmund Y. Lam;
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中图分类 Q811-53;
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Regularization in Super-resolution Reconstruction of Biomedical Images using Gradient Vector Field

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