RUSSIAN

MSU Deinterlacer

MSU Graphics & Media Lab (Video Group)

Take a look at this article on the new site! Follow the link
https://videoprocessing.ai/video_filters/deinterlacing.html

Project: Dr. Dmitriy Vatolin
Implementation, ideas: Maxim Makhinya

Most video sources have interlaced formats (DVD video, Digital video cameras, most standard television transmissions including HDTV, PAL, SECAM etc.). However, most modern video display technologies are progressive based (Plasma panels; LCD TV; CRT High Frequency TV; CRT, LCD displays etc.) and have difficulty displaying interlaced formats. That is why the proper transformation, called de-interlacing, is necessary. We designed a new high quality de-interlacing algorithm. This is a full-fps de-interlacer i.e. it produces one frame for each field (for example, it converts 25i -> 50p), so temporal stability and interpolation of low angle edges was even more attended. Moreover this algorithm is totally automatic. Some comparisons of our algorithm to other methods can be found below.

Results

We have tested our deinterlacer using following sequences: Tennis, Schumacher and Flag (see screenshots below):

screenshot from Tennis sequence
Tennis sequence		 screenshot from Shumacher sequence
Shumacher sequence		 screenshot from Flag sequence
Flag sequence


Here are zoomed parts of frames from Tennis and Schumacher sequences:

Original Part of frame 36 from Tennis
Original Part of frame 36 from Tennis

Smooth Deinterlacing for frame 36 from Tennis
Smooth Deinterlacing		 Proposed Deinterlacing for frame 36 from Tennis
Proposed		 Smart Deinterlace for frame 36 from Tennis
Smart Deinterlace

Original Part of frame 20 from Schumacher
Original Part of frame 20 from Schumacher

Smooth Deinterlacing for frame 20 from Schumacher
Smooth Deinterlacing		 Proposed Deinterlacing for frame 20 from Schumacher
Proposed		 Smart Deinterlace for frame 20 from Schumacher
Smart Deinterlace


This example shows considerable advantage of the proposed method over Smooth Deinterlacer and Smart Deinterlace on diagonal edges.
We have also compared our deinterlacer to commercial solutions. The following example demonstrates our advantage in a really hard case - YV12 interlaced source:
Boolet Deinterlacer for frame 67 from Flag
Boolet Deinterlacer		 FieldsKit Deinterlacer for frame 67 from Flag
FieldsKit Deinterlacer		 HiCon Deinterlacer for frame 67 from Flag
HiCon Deinterlacer		 Proposed Deinterlacer for frame 67 from Flag
Proposed


Our algorithm has also a big advantage on low angle edges:
Boolet Deinterlacer for frame 184 from Flag
Boolet Deinterlacer		 FieldsKit Deinterlacer for frame 184 from Flag
FieldsKit Deinterlacer		 HiCon Deinterlacer for frame 184 from Flag
HiCon Deinterlacer		 Proposed Deinterlacer for frame 184 from Flag
Proposed

References

1. Boolet Deinterlacer - RED GIANT Software Deinterlacing
2. FieldsKit Deinterlacer - RE:Vision Effects, Inc. Deinterlacing
3. HiCon Deinterlacer - Fraunhofer Institut HHI Deinterlacing
4. Smooth Deinterlacing - Smooth Deinterlacing by Gunnar Thalin v.1.1
5. Smart Deinterlace - Smart Deinterlace by Donald Graft v.2.8 beta 1

Download

Please contact us if you are interested in a commercial license.

E-mail:  

Previous Deinterlacing project: MSU-Samsung Deinterlacing Project

Other resources

Video resources:

3D and stereo video
Projects on 3D and stereo video processing and analysis
MSU Video Quality Measurement tools
Programs with different objective and subjective video quality metrics implementation 		Codecs comparisons
Objective and subjective quality evaluation
tests for video and image codecs
Ext. link: x264 parameters efficiency comparison
Public MSU video filters
Here are available VirtualDub and AviSynth filters. For a given type of digital video filtration we typically develop a family of different algorithms and implementations. Generally there are also versions optimized for PC and hardware implementations (ASIC/FPGA/DSP). These optimized versions can be licensed to companies. Please contact us for details via video(at)graphics.cs.msu_ru. 		Filters for companies
We are working with Intel, Samsung, RealNetworks and other companies on adapting our filters other video processing algorithms for specific video streams, applications and hardware like TV-sets, graphics cards, etc. Some of such projects are non-exclusive. Also we have internal researches. Please let us know via video(at)graphics.cs.msu_ru if you are interested in acquiring a license for such filters or making a custom R&D project on video processing, compression, computer vision.
Video codecs projects
Different research and development
projects on video codecs 		Other
Other information
Last updated: 12-May-2022

Server size: 8069 files, 1215Mb (Server statistics)

Project updated by
Server Team and MSU Video Group

Project sponsored by YUVsoft Corp.

Project supported by MSU Graphics & Media Lab