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Computer Engineering Kyungpook National University High-Performance Low-Complexity High-Performance Low-Complexity Bit-Plane coding scheme for MPEG-4 Bit-Plane coding scheme for MPEG-4 FGS FGS 2006. 11. 16 mhchoi@netop ia.knu.ac.kr 200627 9007 최 최 최

Computer Engineering Kyungpook National University High-Performance Low-Complexity Bit-Plane coding scheme for MPEG-4 FGS 2006. 11. 16 [email protected]

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Computer EngineeringKyungpook National University

High-Performance Low-ComplexityHigh-Performance Low-ComplexityBit-Plane coding scheme for MPEG-Bit-Plane coding scheme for MPEG-

4 FGS4 FGS

2006. 11. 16

[email protected]

2006279007 최 민 호

Computer EngineeringKyungpook National University 2

Abstract

Introduction

Bit-Plane coding scheme of MPEG-4 FGS

The proposed coding scheme

Experimental results

Conclusion

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AbstractAbstract

Present a novel and effective bit-plane coding technique

Three superiorities Better video quality in about 1.2 dB in terms of

average PSNR Less memory requirement Lower implementation complexity and power

dissipation.

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(( 참고참고 ) PSNR) PSNR

Peek signal to noise rate 화질의 객관적 평가기준 SNR 을 구할 때는 10log( 신호전력 / 잡음전력 )

으로구합니다 . 이 때 신호전력과 잡음전력은 모두 " 평균전력 " 을 의미

PSNR 은 평균전력을 이용하지 않고 peak 전력을 이용하여 SNR 을 계산하는 것 신호에 순간적으로 나타날 수 있는 최대 전력으로

계산하는 것

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IntroductionIntroduction

Be required to stream to heterogeneous users over various network bandwidths.

In a real situation, the transmission network has the bandwidth limitation. The transmission quality is not guaranteed.

Motivation Develop a bit-plane coding scheme, named

adaptive bit-plane coding, for efficiently encoding the MPEG-4 FGS enhancement layer

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Bit-Plane coding scheme of MPEG-4 Bit-Plane coding scheme of MPEG-4 FGSFGS

The block diagram of MPEG-4 FGS encoder

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MPEG-4 FGS frameworkMPEG-4 FGS framework

FGS : fine granular scalability Base layer uses non-scalable coding to

reach the lower bound of the bit-rate range.

Enhancement layer codes the difference between the original and the reconstructed picture using bit plane coding of DCT coefficients.

Bit stream of FGS enhancement layer may be truncated into any number of bits

Enhances base layer using partial information from enhancement layer

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Bit-Plane codingBit-Plane coding

1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, … ,0,0 (MSB)

0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0, … ,0,0 (MSB-1)

1,0,1,0,0,1,0,1,1,0,0,1,0,0,0,0, … ,0,0 (MSB-2)

0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0, … ,0,0 (MSB-3)

10,0,6,0,0,3,0,2,2,0,0,2,0,0,1,0, … ,0,0 (absolute)

0,x,1,x,x,1,x,0,0,x,x,1,x,x,0,x, … ,x,x (sign bits)

(0,1)

(2,1)

(0,0)(1,0)(2,0)(1,0)(0,0)(2,1)

(5,0)(8,1)

after zigzag ordering

Max value=104 bit planes

(RUN,EOP)symbols

Can get up to 20% bit savings over run-length coding

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DCT (discrete cosine transform)DCT (discrete cosine transform) DCT 를 이용하면 영상을 공간영역 (Spatial Domain) 으로부터 주파수

영역 (Frequency Domain) 으로 변환할 수 있으며 영상 데이터는 변화가 적으므로 낮은 주파수 , 특히 0 주파수 (DC) 성분이 큰 값을 갖게 되고 높은 주파수 성분은 상대적으로 매우 작은 값을 갖게 된다 .

대부분의 정보가 낮은 주파수쪽으로 몰리게 되므로 다음에 설명할 양자화 과정을 적절히 거치면 높은 압축률로 우수한 화질을 얻을 수 있다 .

정보량이 많아 값이 낮은 주파수 성분만을 충실히 취하고 높은 주파수 성분은 값이 아주 작으므로 거의 무시해 버림으로써 전체 데이터 양을 줄이는 원리인데 , 높은 주파수 성분은 영상의 세밀한 해상도에 기여하기 때문에 이런 방법을 사용해 심하게 압축하면 해상도 저하라는 불이익을 감수해야 한다 .

많은 곱하기와 더하기가 사용되므로 계산량이 상당히 많으나 , 고속 알고리즘으로 인해 영상을 8*8 블럭으로 나눠 계산함으로써 계산 효율을 높일 수 있다 .

성능과 실제 구현성이 좋아 정지 영상 뿐 아니라 동영상 압축에서도 폭 넓게 사용되고 있다 .

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MPEG-4 FGS encoderMPEG-4 FGS encoder

FGS encoder structure

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MPEG-4 FGS encoderMPEG-4 FGS encoder

Base Layer bitstream is generated as in a conventional video coding loop

FGS enhancement encoder takes the original and reconstructed DCT coefficients as input and produces FGS enhancement bitstream Bit plane data of DCT coefficient is extracted and scanned with zi

gzag order Block “BP Shift” performs bit-plane alignment among coefficients Block “Find max” finds the highest bit plane within a frame which i

s not all zero to determine the maximum number of bit planes for the VOP

After bit-plane coding the (RUN,EOP) symbols are coded using VLC tables

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MPEG-4 FGS decoderMPEG-4 FGS decoder

FGS decoder structure

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MPEG-4 FGS decoderMPEG-4 FGS decoder Bitstream at the input of an FGS enhancement decoder is

a truncated version of the output bitstream of an FGS enhancement encoder.

Bit plane decoding procedure Initialize the absolute values of all the residues to zeros Perform variable length decoding of (RUN, EOP) symbols

Run is represented with 6 bits ( for values from 0 to 63 ) EOP is a 1-bit flag ,end of the bitplane is reached (1) or not (0) Bitplane contains all zeros if the ALL-ZERO symbol is decoded

After decoding all bits for the FGS VOP available to the FGS decoder, partial absolute values of all residues are obtained

Sign bit is decoded from the enhancement layer bitstream immediately after the (RUN, EOP) code corresponding to the MSB of the non-zero residue

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Proposed coding schemeProposed coding scheme

While the bits distribution is uniformly distributed, the coding efficiency using a combination of run-length and VLC is low.

Properties There are seldom coefficients containing the

symbol ‘1’ in the higher bit-planes. For the lower bit-planes, the symbol distribution

of ‘1’ and ‘0’ is distributed uniformly The front coefficients of the middle bit-planes

contain many symbols ‘1’, but there are some sparse symbols ‘1’ in the rear coefficients of the middle bit-plane.

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Proposed coding schemeProposed coding scheme

Division into three coding modes Since the occurrence probability of the symbol

of ‘0’ and ‘1’ has different properties in different planes, adopt three different compression modes to encode different planes according to above properties. Bypass – all input bits are bypass straightly to output Hybrid – for the middle bit-planes Coordination - to encode the bit-plane with sparse ‘1’

efficiently

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Flow diagram of adaptive bit-plane coding Flow diagram of adaptive bit-plane coding schemescheme

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Experimental resultsExperimental results

PSNR performance of Akiyo sequencePSNR performance of Foreman sequence

Comparison of different FGS designs

[3] “A bitplane coding scheme of MPEG-4 FGSwith high efficiency based on the distribution ofsignificant coefficients“, 2002[4] “Context-based adaptive binary arithmeticcoding in the H.264/AVC video compression Standard”, 2003

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Conclusion Conclusion

Memory size and power reductions are important for hardware design.

In this paper, reduce significant area and power consumption

Improve coding efficiency Due to using either bypass or

coordination compression simplify structure High-speed Low-complexity Low-power