Infognition Super Resolution plugin for VirtualDub resizes video using Super Resolution approach: by accumulating information from previous frames it can provide much more details than any other resizing method.
13 Dec 2013: version 2.0 released. Changes:
New Super Resolution is ready.
December 13, 2013
This year we explored ways to accelerate and improve our Super Resolution engine, and overall research, development and testing took much more time than we anticipated but finally the new engine is available to our users. Today we're releasing it in a form of VirtualDub plugin. DirectShow filter is also ready, so after we change Video Enhancer to use the new version there will be an update for Video Enhancer too. Also, an AviSynth plugin will be released soon. Our advances in speed allow using it in video players to upsize videos to HD in real time on modern PCs and laptops.
Generally quality and speed depend on source video and your CPU'a abilities, but here's an example of changes between our old VirtualDub plugin (1.0) and the new one (2.0) on a particular file (panasonic4.avi) when upsizing from 960x540 to 1920x1080 on an old Quad Core 2.33 GHz:
Quality, in dB of Y-PSNR (higher is better):
version old new fast mode 41.70 42.28 slow mode 42.07 42.73 Time of upsizing 200 frames, in seconds: version old new_rgb new_yv12 fast mode 19.6 14.4 10.3 slow mode 28.7 19.5 14.0 Version 1.0 worked only in RGB32, so for YUV the speed was about the same as for RGB. As you may see, the new version's fast mode provides similar quality to old version's high-quality mode but does it 2-3 times faster depending on color space. And new version's high-quality mode is still faster than old one's fast mode. To achieve these speed gains our SR implementation was rewritten from scratch to work block-wise instead of frame-wise. This way it doesn't need so much memory to store intermediate results and intermediate data never leaves CPU cache, avoiding spending so much time on memory loads and stores. Also, we learned to use SSE2 vector operations better. Unfortunately even in 2013 compilers still generally suck at vectorizing code, so it requires a lot of manual work.
http://www.infognition.com/super_resolution_vdf/
13 Dec 2013: version 2.0 released. Changes:
- Works 1.5 - 3 times faster than 1.0 (reaches real time in YV12 and fast mode).
- Slightly higher quality (+0.5 dB PSNR).
- Natively supports YV12, YUY2 as well as RGB24 and RGB32. The YUV modes work 1.5 times faster than RGB, so when used as a first filter in a chain and decoding source video to YUV works much faster than older version (~2 times faster).
- Adjustable parallelism, simpler quality settings
New Super Resolution is ready.
December 13, 2013
This year we explored ways to accelerate and improve our Super Resolution engine, and overall research, development and testing took much more time than we anticipated but finally the new engine is available to our users. Today we're releasing it in a form of VirtualDub plugin. DirectShow filter is also ready, so after we change Video Enhancer to use the new version there will be an update for Video Enhancer too. Also, an AviSynth plugin will be released soon. Our advances in speed allow using it in video players to upsize videos to HD in real time on modern PCs and laptops.
Generally quality and speed depend on source video and your CPU'a abilities, but here's an example of changes between our old VirtualDub plugin (1.0) and the new one (2.0) on a particular file (panasonic4.avi) when upsizing from 960x540 to 1920x1080 on an old Quad Core 2.33 GHz:
Quality, in dB of Y-PSNR (higher is better):
version old new fast mode 41.70 42.28 slow mode 42.07 42.73 Time of upsizing 200 frames, in seconds: version old new_rgb new_yv12 fast mode 19.6 14.4 10.3 slow mode 28.7 19.5 14.0 Version 1.0 worked only in RGB32, so for YUV the speed was about the same as for RGB. As you may see, the new version's fast mode provides similar quality to old version's high-quality mode but does it 2-3 times faster depending on color space. And new version's high-quality mode is still faster than old one's fast mode. To achieve these speed gains our SR implementation was rewritten from scratch to work block-wise instead of frame-wise. This way it doesn't need so much memory to store intermediate results and intermediate data never leaves CPU cache, avoiding spending so much time on memory loads and stores. Also, we learned to use SSE2 vector operations better. Unfortunately even in 2013 compilers still generally suck at vectorizing code, so it requires a lot of manual work.
http://www.infognition.com/super_resolution_vdf/