MSU Lossless Video Codec
{{short description|Video codec}}
{{Infobox software
| name = MSU Lossless Video Codec
| screenshot = 300px
| developer = {{nowrap|Dmitry Vatolin}}, {{nowrap|Dmitry Popov}}, {{nowrap|Sergey Putilin}}
| discontinued = yes
| latest preview version = 0.6.0
| latest preview date = {{Start date and age|2005|9|19|df=no}}
| programming language = C++
| operating system = Microsoft Windows
| platform = IA-32
| size = {{nowrap|157 KB}}
| language = English
| genre = lossless video codec
| license = Proprietary, free for {{nowrap|non-commercial}} use
| website = {{URL|http://www.compression.ru/video/ls-codec/index_en.html}}
}}
The MSU Lossless Video Codec is a video codec developed by the Graphics & Media Lab Video Group of Moscow State University. It was designed to provide space-effective lossless video compression. As of 2007 MSU had the second-best compression ratio when compared to many other lossless video codecs,{{citation
|title = Lossless Video Codecs Comparison 2007
|url = http://compression.ru/video/codec_comparison/lossless_codecs_2007_en.html
|work = MSU Graphics & Media Lab (Video Group)
|year = 2007
|access-date = 2011-12-07
}} with the better result shown by YULS codec.
Description
MSU Lossless Video Codec is available as a Video for Windows codec. It can be used from such applications as VirtualDub or Adobe Premiere. Possible input formats are RGB24 (RGB), RGB32, YUY2, YUYV and YV12.
The codec is available free of charge for non-commercial use. {{asof|2011|11|23}} the commercial license and the source code of this codec is unavailable.
Despite its name, the codec has several lossy modes.
Release history
class="wikitable" |
Version || Date || Changes |
---|
0.6.0
| {{dts|2005|9|19}} |
|
0.5.8
| {{dts|2005|3|20}} |
|
0.5.6
| {{dts|2005|2|14}} |
|
0.5.2
| {{dts|2005|2|6}} | |
0.2.4p
| {{dts|2004|10|1}} |
|
0.2.4
| {{dts|2004|9|24}} |
|
References
{{reflist}}
{{Compression formats}}
{{Compression Software Implementations}}
{{DEFAULTSORT:Msu Lossless Video Codec}}
Category:Lossless compression algorithms
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