摘要： 采用非线性扩散模型建立超分辨率图像重构的偏微分方程，利用各向异性扩散方程的方向选择平滑的特性，在重构高分辨率图像的同时能够很好地消除系统噪声，保持细节信息。实验结果表明，该方法有效地提高了重构的图像质量，在视觉观察和数值评价上都优于原有正则化方法，并且对不同噪声水平的图像具有很好的鲁棒性。

关键词: 超分辨率图像重构, 正则化方法, 偏微分方程, 各向异性扩散

Abstract: From the typical anisotropic diffusion equations, the PDEs for image super-resolution are deduced and, then a robust regularization-type reconstruction algorithm is devised. The proposed approach can suppress the system noise and preserve more details of the estimated HR image by orientation-selective regularization. The experimental results show that the PDE-based approach makes a promising progress in image super-resolution. It outperforms the previous methods in both numerical and perceived visual quality and is robust to noisy images.

Key words: image super-resolution, regularization technique, partial differential equation(PDE), anisotropic diffusion

中图分类号: 

• TP391