Experimental study on scan order and motion compensation in lossless video coding Telematics/Network Engineering
Feb 14, 2016
Experimental study on scan order and motion compensation in lossless
video coding
Telematics/Network Engineering
Scan order and motion compensation in lossless coding
School of Telematics and Network EngineeringCarinthia Tech Institute, Austria
Team of students: Stefan A. KramatschAgnes 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
Team
Motivation
Basics
Realization
Results
Conclusion
Structure
Presentation Outline
Semester Project in Compression Techniques 2
Alternative way to view videos
Make data compression more concrete
Experience usage of programming languages in picture processing
Project goals
Motivation
Mainly used in medical applications – required by legalregulation
JPEG, JPEG-LS, lossless JPEG 2000 on per-frame basis
Temporal redundancy ignored no motion compensation limited compression performance
Lossless video coding
Basics(1)
Classical view of video data
Basics(2)
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
Classical view of video data
Basics(3)
Different views on the video block
Normal
View
Ver
tical
Vie
w
Horizontal View
Basics(4)
Normal view Horizontal view Vertical view
Different views on the video block
Basics(5)
Frame 40 Frame 112 Frame 112
Scan order
Basics(6)
File seen as a stream of gray valuesWritten to a .txt file
File compressors used:- Arithmetical coder- Runlength Encoding (RLE)- Huffman Coding
Streams – stream compression
Basics(7)
Scene divided into non-overlapping “block“ regionsCompare blocks (current <-> reference frame)
motion vector for each block“Best“ match based on mean square error
Stored as prediction
Current frame – prediction = residual frame to be compressedCommon for lossy compression
Motion compensation – Block matching
Basics(8)
Usage in lossless codingNormally temporal based now spatially
Motion compensation – Block matching
Basics(9)
Reference Frame 1 Residual Frame 40
Frame 112 non BM and BM
Horizontal View Vertical View
Frame 112 non BM and BM
Input: all frames of a video (in .pgm format)
Build the 3D video blockCut normally, vertically and horizontallyWith or without blockmatchingFrame based or stream based computing
Implemented in c++
Implementation
Realization(1)
Matlab application
Based on one reference frame all remaining: residual frames
Searchwindow 32x32 PixelsBlocksize 16x16 PixelsSimilar Block search based on Root Mean Square
Implementation of block matching
Realization(2)
JPEG 2000 Lossless mode
Java Implementation: JJ2000 (http://jj2000.epfl.ch)
Standard options except:Lossless Mode (“ –lossless on “)Cancel console output (“ –verbose off “)
Lossless frame compression
Realization(3)
Akiyo (176 x 144 x 300) – low movementCarphone (176 x 144 x 383) – high movementClaire (176 x 144 x 494) – low movementFootball (720 x 486 x 60) – high movementForeman (176 x 144 x 49) – high movementGrandma (176 x 144 x 871) – low movementMobile (720 x 576 x 40) – high movementMother and Daughter (176 x 144 x 962) – low movementSalesman (176 x 144 x 449) – low movement
Testvideos (Spatial x Temporal resolution)
Realization(4)
Compression Ratio
Results
Low movement High Movement Stream
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
Without Blockmatching
Conclusion(1)
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
With Blockmatching
Conclusion(2)
Thank you for your attention!
Telematics/Network Engineering