提出了一种能够克服匹配误差的红外图像超分辨率算法。该算法采用了多通道自适应正规技术来处理由于红外图像匹配不精确而引起的病态问题。由于每幅低分辨率图像的匹配误差都不相同, 因此每个通道的正规参数都自适应地被正规参数函数选择。提出的算法能够在没有任何先验信息的情况下对于图像匹配误差具有很强的鲁棒性。随着迭代过程的进行每个正规参数以及重建的图像不断地被更新。实验结果表明该算法相比传统算法在客观量度和视觉效果两个方面都具有较好性能。

This paper proposes an infrared images super-resolution algorithm which is insensitive to image registration error. The proposed method mainly applies a multichannel regularized technology to handle the ill-posed problems introduced by the infrared image registration error. Since the registration error in each low-resolution image has a different pattern, the regularization parameters are determined adaptively for each channel. The proposed algorithm is robust against the image registration error and it does not require any prior information. The regularization parameters and estimated high-resolution images are updated with the progress of iteration. The performance of the proposed method is validated by implementing a series of experiments. The experimental results show the proposed algorithm performs better than the conventional method, both in quantitative terms and in visual effects.