A pioneering video-to-video super-resolution reconstruction algorithm based on segmentation and space–time regularisation

Abstract

In view of the common existing problems in present video-to-video super-resolution reconstruction, this paper proposes a pioneering video-to-video super-resolution reconstruction algorithm based on segmentation and space–time regularisation to solve these problems. First, a video-to-video super-resolution reconstruction algorithm based on segmentation is proposed to eliminate reconstructed temporal ringing and to improve the times of reconstruction. Second, considering that image mosaic is involved in our proposed reconstruction algorithm, an improved fade-in and fade-out method is proposed to make the mosaic image looks more natural. At last, an improved space–time regularisation algorithm is put forward to remove noise and preserve image edge at the same time. Using several experiments, we prove that the proposed algorithm can achieve state-of-the -art reconstruction effect.

Keywords:

• Video-to-video super-resolution reconstruction algorithm
• Segmentation
• Image mosaic
• Bilateral total variation
• Space–time regularisation

Acknowledgements

The work is supported by National Natural Science Fund of china (61071161), NSAF (11176018), Science Research Program of Hubei Provincial Department of Education of china (Q20111907), Science Research Program of Sichuan Provincial Department of Education of China (11ZB073) and Science Research Program of Visual Computing and Virtual Reality Key Laboratory of Sichuan Province (PJ201113). Natural Science Fund of Hubei Province (No.2012FFC02601).