Automatic, Efficient, Temporally-Coherent Video Enhancement for Large Scale Applications
Abstract
A fast and robust method for video contrast enhancement is presented.
The method uses the histogram of each frame, along with upper and lower
bounds computed per shot in order to enhance the current frame. This
ensures that the artifacts introduced during the enhancement is reduced
to a minimum. Traditional methods that do not compute per-shot estimates
tend to over-enhance parts of the video such as fades and transitions.
Our method does not suffer from this problem, which is essential for a
fully automatic algorithm. We present the parameters for our methods
which yielded the best human feedback, which showed that out of 208 videos,
203 were enhanced, while the remaining 5 were of too poor quality to
be enhanced. Additionally, we present a visual comparison of our work with
the recently-proposed Weighted Thresholded Histogram Equalization (WTHE) algorithm.
The method uses the histogram of each frame, along with upper and lower
bounds computed per shot in order to enhance the current frame. This
ensures that the artifacts introduced during the enhancement is reduced
to a minimum. Traditional methods that do not compute per-shot estimates
tend to over-enhance parts of the video such as fades and transitions.
Our method does not suffer from this problem, which is essential for a
fully automatic algorithm. We present the parameters for our methods
which yielded the best human feedback, which showed that out of 208 videos,
203 were enhanced, while the remaining 5 were of too poor quality to
be enhanced. Additionally, we present a visual comparison of our work with
the recently-proposed Weighted Thresholded Histogram Equalization (WTHE) algorithm.
Research Areas
