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Experimental study on scan order and motion compensation in lossless video coding ... basis for motion compensated hybrid coding. basis for application of 3D ... – PowerPoint PPT presentation

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Title: PowerPoint-Pr


1
Telematics/Network Engineering
Experimental study on scan order and motion
compensation in lossless video
coding
2
Scan order and motion compensation in lossless
coding
Team
  • School of Telematics and Network Engineering
  • Carinthia Tech Institute, Austria
  • Team of students Stefan A. Kramatsch
  • Agnes Gruber, Alexander Krapesch, Stefan
    Matschitsch, Thomas Mayerdorfer,
  • Stefan Miedl, Stefan Moser, Martin Tschinder,
    Stefan Zorn-Pauli
  • Project leader
  • Dr. Andreas Uhl
  • Head of School
  • Dr. Herbert Stögner

3
Presentation Outline
Structure
  • Motivation
  • Basics
  • Realization
  • Results
  • Conclusion

4
Motivation
Project goals
  • Semester Project in Compression Techniques 2
  • Alternative way to view videos
  • Make data compression more concrete
  • Experience usage of programming languages in
  • picture processing

5
Basics(1)
Lossless video coding
  • Mainly used in medical applications required
    by legal
  • regulation
  • JPEG, JPEG-LS, lossless JPEG 2000 on per-frame
    basis
  • Temporal redundancy ignored
  • ? no motion compensation
  • ? limited compression performance

6
Basics(2)
Classical view of video data
7
Basics(3)
Classical view of video data
  • Temporally ordered still images
  • Frames are similar
  • ? basis for motion compensated hybrid coding
  • ? basis for application of 3D video techniques
  • Possible to form a 3D block of video data

8
Basics(4)
Different views on the video block
9
Basics(5)
Different views on the video block
  • Normal view Horizontal view Vertical view

Frame 40 Frame 112 Frame 112
10
Basics(6)
Scan order
11
Basics(7)
Streams stream compression
  • File seen as a stream of gray values
  • Written to a .txt file
  • File compressors used
  • - Arithmetical coder
  • - Runlength Encoding (RLE)
  • - Huffman Coding

12
Basics(8)
Motion compensation Block matching
  • Scene divided into non-overlapping block
    regions
  • Compare blocks (current lt-gt reference frame)
  • ? motion vector for each block
  • Best match based on mean square error
  • ? Stored as prediction
  • Current frame prediction residual frame
  • to be compressed
  • Common for lossy compression

13
Basics(9)
Motion compensation Block matching
  • Usage in lossless coding
  • Normally temporal based
  • ? now spatially

Reference Frame 1 Residual Frame 40
Vertical View
Horizontal View
Frame 112 non BM and BM
Frame 112 non BM and BM
14
Realization(1)
Implementation
  • Input all frames of a video (in .pgm format)
  • Build the 3D video block
  • Cut normally, vertically and horizontally
  • With or without blockmatching
  • Frame based or stream based computing
  • Implemented in c

15
Realization(2)
Implementation of block matching
  • Matlab application
  • Based on one reference frame
  • all remaining residual frames
  • Searchwindow 32x32 Pixels
  • Blocksize 16x16 Pixels
  • Similar Block search based on Root Mean Square

16
Realization(3)
Lossless frame compression
  • JPEG 2000 Lossless mode
  • Java Implementation JJ2000 (http//jj2000.epfl.ch
    )
  • Standard options except
  • Lossless Mode ( lossless on )
  • Cancel console output ( verbose off )

17
Realization(4)
Testvideos (Spatial x Temporal resolution)
  • Akiyo (176 x 144 x 300) low movement
  • Carphone (176 x 144 x 383) high movement
  • Claire (176 x 144 x 494) low movement
  • Football (720 x 486 x 60) high movement
  • Foreman (176 x 144 x 49) high movement
  • Grandma (176 x 144 x 871) low movement
  • Mobile (720 x 576 x 40) high movement
  • Mother and Daughter (176 x 144 x 962) low
    movement
  • Salesman (176 x 144 x 449) low movement

18
Results
Compression Ratio
Low movement High Movement Stream
19
Conclusion(1)
Without Blockmatching
  • Improved frame based compression by alternative
    views
  • Exploitation of spatial instead of temporal
    redundancies through alternative scan order
  • Little computational demand compared to BM
  • Increased memory demand and coding delay
  • Stream compression has little effect

20
Conclusion(2)
With Blockmatching
  • The increase of compression ratio does not
    justify the usage of BM algorithms in case of
    alternative views
  • Superior results for 1D based compression
    algorithms

21
Telematics/Network Engineering
Thank you for your attention!
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