Region-Based Temporally Consistent Video Post-Processing

Xuan Dong, Boyan Bonev, Yu Zhu, Alan L. Yuille; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, pp. 714-722


We study the problem of temporally consistent video post-processing. Previous post-processing algorithms usually either fail to keep high fidelity or fail to keep temporal consistency of output videos. In this paper, we observe experimentally that many image/video enhancement algorithms enforce a spatially consistent prior on the enhancement. More precisely, within a local region, the enhancement is consistent, i.e., pixels with the same RGB values will get the same enhancement values. Using this prior, we segment each frame into several regions and temporally-spatially adjust the enhancement of regions of different frames, taking into account fidelity, temporal consistency and spatial consistency. User study, objective measurement and visual quality comparisons are conducted. The experimental results demonstrate that our output videos can keep high fidelity and temporal consistency at the same time.

Related Material

author = {Dong, Xuan and Bonev, Boyan and Zhu, Yu and Yuille, Alan L.},
title = {Region-Based Temporally Consistent Video Post-Processing},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2015}