Super-resolution reconstruction of MR image based on structure-adaptive normalized convolution

To improve the signal-to-noise ratio and the resolution of MR image, this paper introduce structure-adaptive normalized convolution algorithm for image reconstruction from a series of repeatedly scanned MR images. The algorithm is based on the normalized convolution, which makes use of the local structure information to adjust filter parameters. Experimental results show that the algorithm can effectively enhance the resolution of image, while preserving the edge and detail of image.