MSU Video Super-Resolution Filter
Filter for high-quality video resolution enhancement
- Method ideas: Dr. Dmitriy Vatolin
- Implementation: Artem Titarenko
This filter increases resolution of video sequence while saving and improving details and reducing artifacts.
Main problems of the current approach:
- Fixed zooming factor (two times). Later it will be generalized.
- No scene change detection.
- Processing speed is considerably higher than for other SuperResolution approaches known to us
- Upscaling factor should be a power of 2. Other scaling factors are also possible, but they result in a relatively lesser quality of video due to use of additional common resampling algorithm
- Different presets with various speed/quality trade-off
- Processing is fully automatic
- Processing can be totally consecutive without look ahead at future frames
- There is a special algorithm for noisy video upscaling which gives smoother images of better visual quality
Since the output resolution of video is very large only parts of sequences are shown.
The first example is from “stefan” sequence:
Topaz Enhance SR
The next example is from “news” sequence:
“news”, source video and video processed with MSU Super-Resolution filter
(video is here, 974 KB)
Fragment of the “toy” sequence:
“toy”, source video and video processed with MSU Super-Resolution filter
(video is here, 660 KB)
Please read MSU filters FAQ before mailing.
MSU Benchmark Collection
- MSU Video Upscalers Benchmark 2022
- MSU HDR Video Reconstruction Benchmark 2022
- MSU Super-Resolution for Video Compression Benchmark 2022
- MSU Video Quality Metrics Benchmark 2022
- MSU Video Alignment and Retrieval Benchmark
- MSU Mobile Video Codecs Benchmark 2021
- MSU Video Super-Resolution Benchmark
- MSU Shot Boundary Detection Benchmark 2020
- MSU Deinterlacer Benchmark
- The VideoMatting Project
- Video Completion
- Codecs Comparisons & Optimization
- Video Quality Measurement Tool 3D
MSU Datasets Collection
- Video Filters