| 英文标题 | Medical image super-resolution reconstruction based on neighborhood regression |
| 作者英文名 | Duanmu Chunjiang, Shen Biting |
| 机构英文名 | a.School of Physics & Electronic Information Engineering,b.School of Mathematics & Computer Science,Zhejiang Normal University,Jinhua Zhejiang 321004,China |
| 英文摘要 | This paper proposed a super-resolution method based on neighborhood regression of internal examples, in order to improve the resolution of medical images. First, it treated the input low-resolution image as a high-resolution image to construct an internal image training set based on its own instance, no longer dependent on the external training set. Then, it divided the high-resolution reconstruction into high-frequency reconstruction and low-frequency reconstruction, neighborhood regression method reconstructed the high-frequency detail part of the image, and bicubic interpolation method reconstructed the low-frequency part. Finally, iterative combination method combined the high-frequency component and the low-frequency component to get a high-resolution image of the final output. The experimental results show that the proposed method outperforms the traditional super-resolution reconstruction algorithm, and the reconstructed medical image visual effect is more realistic. |
| 英文关键词 | super resolution; neighborhood regression; high frequency reconstruction; low frequency reconstruction |