IN TER N ATIO N A L C O N F ER EN C E O N TELEC O M M U N IC AT IO N S, 2 00 9 . IC T ' 09 .

TA R EK O U N IWA L ID AY ED I

M O H A M ED A BID

N ATIO N A L EN G IN EER IN G SC H OO L O F S FA X

New Low Complexity DCT Based Video Compression Method

Outline

IntroductionDCT based coding methodProposed methodExperimentsConclusion

Introduction

Video signal has high temporal redundancies due to the high correlation between successive frames.

Current video compression technics are not suitable for exploiting this redundancy.

This paper presents a new video compression approach exploiting the temporal redundancy in the video frames. improve compression efficiency with minimum processing complexity

Introduction

This paper consists on a 3D to 2D transformation of the video frames that allows exploring the temporal redundancy. avoiding the computational MC step.

The transformation turns the spatial-temporal correlation into high spatial correlation. e.g, transforms each group of pictures to one picture

Decorrelation of the resulting pictures by the DCT energy compaction high video compression ratio

Introduction

The proposed method is efficient especially in high bit rate and with slow motion video.

The proposed method is suitable for video surveillance applications embedded video compression systems

Problem

Motion estimation process is computationally intensive. stored video applications. off-line on powerful computers.

Not appropriate to be implemented as a real-time for video surveillance camera fully digital video camera

Solution

Improve compression efficiency Temporal redundancies are more relevant than spatial one. Exploiting more redundancies in the temporal domain can achieve

more efficient compression.

Minimize processing complexity 3D transform produces video compression ratio

close to the motion estimation based. less complex processing. exploit temporal redundancy.

Outline

IntroductionDCT based coding methodProposed methodExperimentsConclusion

DCT based coding method

Compression energy compaction

DCT based coding method

Undesirable effects1. graininess2. blurring3. blocking artifacts

3D-DCT coding method

The 2D-DCT has the potential of easy extension into the third dimension. e.g, 3D-DCT

3D-DCT includes the time as third dimension into the transformation and energy compaction process.

3D-DCT coding method

In 3-D transform coding based on the DCT, the video is first divided into blocks of M N K pixels. M : horizontal dimension N : vertical dimension K : temporal dimension

Treat video as a succession of 3D blocks or video cubes.

3D-DCT coding method

3-D transform coding method Advantage :

1. do not require the computationally intensive process of motion estimation.

Disadvantage : 1. requires K frame memories both at the encoder and decoder to

buffer the frames.

3D-DCT coding method

3-D based coder v.s Motion compensated coder 3-D based coder :

high compression ratio lower complexity

The proposed method puts in priority the exploitation of temporal redundancy. temporal is more important than spatial.

Outline

IntroductionDCT based coding methodProposed methodExperimentsConclusion

Proposed method

Basic idea is to represent video data with high correlated form. projecting temporal redundancy of each group of pictures into

spatial domain.

Combining them with spatial redundancy in one representation with high spatial correlation.

The obtained representation will be compressed as still image with JPEG coder.

Proposed method

The proposed method step : input the video cube. decompose into temporal frames. gather into one big frame. coding the obtained big frame.

Proposed method

A. Hypothesis many experiences had proved that the variation is much less in

the temporal dimension than the spatial one.

pixels, in 3D video signal, are more correlated in temporal domain than in spatial one.

Expression :

Proposed method

spatial

temporal

Proposed method

B. Accordion based representation temporal and spatial decomposition of video cube.

1

32

4

43 2

1

Proposed method

Proposed method

C. Accordion analytic representation input the GOP frames and output the resulting frame IACC

inverse process :

Proposed method

D. Coding ACC-JPEG decompose the "IACC" frame into 8x8 blocks.

for each 8x8 block : Discrete cosine Transformation (DCT). Quantification of the obtained coefficients. Course in Zigzag of the quantized coefficients. Entropic Coding of the coefficients (RLE, Huffman).

Outline

IntroductionDCT based coding methodProposed methodExperimentsConclusion

Experiments

A. Parameters of the representation

Experiments

B. Compression performance

Experiments

C. ACC-JPEG artifacts

Experiments

Compare to MPEG-4

Outline

IntroductionDCT based coding methodProposed methodExperimentsConclusion

Conclusion

Feature analysis Symmetry Simplicity Objectivity Flexibility

Exploits temporal redundancy with the minimum of processing complexity is suitable in video embedded systems or video surveillance.

Worst compression performance with non-uniform and �fast motion sequence.�