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High quality image and video resampling

MSU Graphics & Media Lab (Video Group)

Researchers:

Alexey Lukin Andrey Krylov Anastasia Koulikova Dmitriy Vatolin Sergey Putilin

At the end of October 2002 we have started the project on "High quality image and video resampling", supported by Samsung Advanced Institute of Technology (http://www.sait.samsung.co.kr/). The project's goal was to design a new high-quality method for resampling of images and video.

The tasks of the project include:

• Design of resampling method.
• Design and implementation of image quality metrics.
• Design of methods and metrics for evaluation of quality of different resampling algorithms and extensive testing of available resampling algorithms.

Our image resampling algorithm, G&M Lab Impress, has the folloing advantages over the standard methods:

• High sharpness of resulting images and good anti-aliasing.
• Adjustable ratio between different resampling artifacts (blurriness, aliasing, ringing).
• Absence of sub-pixel shifts in the resulting image.
• "Extra Sharpness" feature for sharpness increase in the process of resampling.
• Possibility of effective hardware implementation.

Several metrics were implemented during the project (including LUV-metrics accounting for Contrast Sensitivity Function). One metric for measurement of image bluring-sharpening can be particularly interesting for future research.

Extensive testing of different image resampling algorithms has been performed. Seven "mira" test vector images were created for testing tasks. Another 9 photos provided by SAIT were used. These 16 images have been processed using 18 resampling methods, (including methods of well known video-processing tool VirtualDub resampling methods and of Adobe Photoshop 7.0). Totally we have performed more than 1500 measurements for different methods, images and resolutions.

These images are obtained by comparison of scaled image with the original image (rasterized from vector image using Adobe Photoshop). Black color stands for no difference. Blue colors stand for slight differences. Green, yellow and red colors stand for more noticeable, significant differences.

Another resources

Video resources:

Public MSU video filters Here are available VirtualDub and AviSynth filters. Commonly we develop a whole family of some kind of a filter. 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. MSU Cartoon Restore (New!) MSU Noise Estimation MSU Frame Rate Conversion MSU Image Restoration MSU Denoising (Top!) (New!) MSU Old Cinema MSU Deblocking (Top!) MSU Smart Brightness and Contrast (Top!) MSU Smart Sharpen (Top!) MSU Noise generation MSU Noise estimation MSU Motion Estimation Information MSU Subtitles removal MSU Logo removal (Top!) MSU Deflicker (Top!) MSU Field Shift Fixer AviSynth plug-in MSU StegoVideo MSU Cartoonizer (Top!) MSU SmartDeblocking (Top!) MSU Color Enhancement MSU Old Color Restoration MSU filters FAQ (Read me!) MSU filters statistics	MSU 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. Automatic Objects Segmentation Semiautomatic Objects Segmentation New Frame Rate Conversion New Deinterlacer MSU-Samsung Deinterlacing Project Digital TV Signal Enhancement Old Film Recovery Tuner TV Restore Panorama Video2Photo SuperResolution SuperPrecision MSU-Samsung image and video resampling MSU-Samsung Frame Rate Conversion Motion Phase filter Deshaker (video stabilization) Film Grain/Degrain filter Deblurring filter Video Content Search
Codecs comparisons Objective and subjective quality evaluation tests for video and image codecs Options Analysis of Codec x264 (New!) 4-th MPEG4-AVC/H.264 Comparison (Top!) Lossless Video Codecs Comparison 2007 3-rd MPEG4-AVC/H.264 Comparison HD Photo and JPEG 2000 Comparison MPEG-2 Decoders Crash Test (Top!) Subjective Compar. of 4 Modern Codecs (Top!) 2-nd MPEG-4 AVC/H.264 Comparison (Top!) FAQ of 2-nd H.264 Comparison 1-st MPEG-4 AVC/H.264 Codecs Comparison FAQ of 1-st H.264 Comparison JPEG 2000 Image Codecs Comparison (Top!) Lossless Video Codecs Comparison 2004 MPEG-4 SP/ASP Codecs Comparison (Top!) Video codecs comparison (old) Ext. link: x264 parameters efficiency comparison	Video quality metrics Programs with different objective and subjective video quality metrics implementation MSU Video Quality Metric - objective metrics for codecs and filters comparison (Top!) Implemented metrics short info: PSNR, Delta, MSAD, MSE, SSIM, VQM, MSU Blurring, MSU Blocking MSU Brightness Flicking Metric MSU Brightness Independent PSNR MSU Drop Frame Metric MSU Noise Estimation Metric MSU VQM Metric Tool FAQ MSU Human Perceptual Quality Metric - several metrics for exact visual tests (Top!) Implemented metrics short info: ITU-R BT.500-11: DSIS, DSCQS I & II, SCACJ; EBU: SAMVIQ; MSUCQE MSU PVQ Metric Tool FAQ
Video codecs projects Different research and development projects on video codecs MSU Lossless Video Codec (Top!) MSU Screen Capture Lossless Codec (Top!) MSU MPEG-2 Video Codec x264 Codec Improvement	Other Other information Crazy gallery (filters screams :) License for commercial usage of MSU VideoGroup Public Software (please be careful: some soft like metrics has another license!)

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Last updated: 12-October-2007

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Server Team and MSU Video Group

Project sponsored by YUVsoft Corp.

Project supported by MSU Graphics & Media Lab