基于全局运动模型配准的图像超分辨重建

The Image Super-resolution Reconstruction Based on the Global Motion Registration

把全局运动模型配准算法运用到序列图像超分辨重建中,通过与优化的基于频域的配准法进行对比,在运动模型可以准确地反映物体运动状态的情况下,该算法能够更精确地估计运动参数,从而确保重建后的高分辨率图像拥有更多细节信息。同时,阐述了参与重建的低分辨率图像帧数越多,重建精度会越高,但随着帧数的增多,重建误差降低幅度会越低,而算法复杂度及其耗时会过多地增加,因此提出应根据对重建精度的要求而确定参与重建的低分辨率图像的帧数。

The image registration of the global motion model is used successfully to the image super-resolution reconstruction. It can estimate motion parameters more accurately than the optimized registration algorithm in the frequency domain if the motion model is a good approximation to the motion between images, therefore, can insure that the reconstructed high resolution image possesses more details. At the same time, it is expounded that the larger the frame number of the low resolution images is, the more accurate the reconstructed image will be. But with the increasement of the frame number of the LR images, the diversification of the mean square error between the reconstructed image and the real image diminishes, and cost of the algorithm would be increased greatly. So, the frame number of the LR images should be determined according to the precision of the reconstructed image.