A Zero-Value Prediction Technique for Fast DCT Computation
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Transcript of A Zero-Value Prediction Technique for Fast DCT Computation
A Zero-Value Prediction Technique for A Zero-Value Prediction Technique for Fast DCT ComputationFast DCT Computation
Y. Nishida, K. Inoue, and V. MoshnyagaY. Nishida, K. Inoue, and V. Moshnyaga
IntroductionIntroduction Discrete Cosine Transform (DCT) is the most commonly Discrete Cosine Transform (DCT) is the most commonly
used transform for video coding (JPEG, MPEG H26x etc).used transform for video coding (JPEG, MPEG H26x etc).
DCT is a very computationally expensive task.DCT is a very computationally expensive task.
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ProblemProblem
DCT requireDCT requiress a measurable amount of energy a measurable amount of energy and many operations.and many operations.
Reducing the number of operationReducing the number of operationss and energy consumption of and energy consumption of DCT becomeDCT becomess important. important.
Our ProposalOur ProposalA Zero-Value Prediction Technique for Fast DCT A Zero-Value Prediction Technique for Fast DCT
ComputationComputation
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AdvantageAdvantage
RReduceeducess the number of DCT and quantization the number of DCT and quantization operations.operations.RReduceeducess energy consumption. energy consumption.Increases Increases DCT DCT operation operation speed.speed.
DisadvantageDisadvantage
The picture quality deteriorateThe picture quality deterioratess..
The feature of DCTThe feature of DCT
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2222 -6-6 -4-4 00 77 00 -2-2 -3-3
1111 00 55 -4-4 -3-3 44 00 -3-3
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66 22 -1-1 -1-1 -3-3 00 00 88
11 22 11 22 00 22 -2-2 -2-2
-8-8 -2-2 -4-4 11 22 11 -1-1 11
-3-3 11 55 -2-2 11 -1-1 11 -3-3
DCT
The high frequency components at the DCT output are The high frequency components at the DCT output are concentrated nearby zero value.concentrated nearby zero value.
Input data (Pixel Level)Input data (Pixel Level) Output data (DCT coefficient)Output data (DCT coefficient)
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The feature of QuantizationThe feature of Quantization
Quantization Quantization
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-1-1 00 00 00 00 00 00 00
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88 22 11 -3-3 00 11
2222 -6-6 -4-4 00 77 00 -2-2 -3-3
1111 00 55 -4-4 -3-3 44 00 -3-3
22--1010
55 00 00 77 33 22
66 22 -1-1 -1-1 -3-3 00 00 88
11 22 11 22 00 22 -2-2 -2-2
-8-8 -2-2 -4-4 11 22 11 -1-1 11
-3-3 11 55 -2-2 11 -1-1 11 -3-3Input data (DCT coefficient)Input data (DCT coefficient) Quantization output data Quantization output data
In the case Quantization step = 16In the case Quantization step = 16
The probability of elements in the encoding block toThe probability of elements in the encoding block tobecome zero after quantization is very high.become zero after quantization is very high.
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Zero-Value Prediction TechniqueZero-Value Prediction Technique
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In the case with N=2In the case with N=2
The detected string The detected string of zerosof zeros
Starting point ofStarting point ofzero-value predictionzero-value prediction
Reducing Reducing operations for operations for 35 DCT coefficient35 DCT coefficients s is possible.is possible.
The predicted The predicted valuevalue
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When the DCT output N zeros, we predict the remaining When the DCT output N zeros, we predict the remaining result result is is also zero also zero without actual DCT computing.without actual DCT computing.
A Zero-Value Prediction TechniqueA Zero-Value Prediction Technique Example (1/2) Example (1/2)
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1111 00 55 -4-4 -3-3 44 00 -3-3
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66 22 -1-1 -1-1 -3-3 00 00 88
11 22 11 22 00 22 -2-2 -2-2
-8-8 -2-2 -4-4 11 22 11 -1-1 11
-3-3 11 55 -2-2 11 -1-1 11 -3-3
Conventional TechniqueConventional Technique
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A Zero-Value Prediction techniqueA Zero-Value Prediction technique
DCT coefficientDCT coefficient
The prediction The prediction errorerror increases increases but but most of most of the DCT coefficientthe DCT coefficientss will be will be zerozeross after quantization. after quantization. 77
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-1-1 00 00 00 00 00 00 00
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00 00 00 00 00 00 00 00
00 00 00 00 00 00 00 00
Quantization output dataQuantization output data
Prediction mistakePrediction mistake
When a picture is decoded, When a picture is decoded, tthe prediction he prediction errorerror degraddegradeses image quality image quality
A Zero-Value Prediction Technique A Zero-Value Prediction Technique Example (2/2)Example (2/2)
Prediction mistakePrediction mistake
Conventional TechniqueConventional Technique A Zero-Value Prediction techniqueA Zero-Value Prediction technique
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EvaluationEvaluationUsing the MPEG software from MPEG Software Simulation GroupUsing the MPEG software from MPEG Software Simulation Group
Video benchmarksVideo benchmarks
missamissa carpohnecarpohne foremanforeman salesmansalesman
QCIFQCIF QCIFQCIF QCIFQCIF CIFCIF
150frame150frame 382frame382frame 298rame298rame 300rame300rame
2D-DCT algorithm use addition 1024 and multiplication 1024 times 2D-DCT algorithm use addition 1024 and multiplication 1024 times per 1 block. per 1 block. 2D-DCT use partitionable method (1D-DCT×1D-DCT).2D-DCT use partitionable method (1D-DCT×1D-DCT). RRaster scanaster scan order of DCT computation order of DCT computation..
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PSNR as a function of NPSNR as a function of N
The PSNR is low when N is small.The PSNR is low when N is small. The PSNR does not change a lot after N=9.The PSNR does not change a lot after N=9.
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PS
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Operation reduction rate as a function Operation reduction rate as a function of Nof N (( DCTDCT ))
The reduction rate is high when N is small.The reduction rate is high when N is small.
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Operation reduction rate as a function Operation reduction rate as a function of Nof N (( quantizationquantization ))
The reduction rate is high when N is small The reduction rate is high when N is small (similarly to t(similarly to the DCT operationhe DCT operation)). .
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48.75dB48.75dB 47.67dB47.67dB
Original methodOriginal method Zero-value predictionZero-value prediction (( N=9N=9))
The PThe PNSRNSR decreases decreasesby 1.07dB.by 1.07dB.
The example of a pictureThe example of a picture
Assumption toAssumption to accept accept N=9 as a tradeoff for both picture quality aN=9 as a tradeoff for both picture quality and the reduction rate.nd the reduction rate.
Example of reconstructed picture for N=9Example of reconstructed picture for N=9
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ConclusionConclusion
When N=9, the number of computations When N=9, the number of computations is reduced bis reduced by 29% fy 29% for DCT and by 59% for quantization.or DCT and by 59% for quantization.
The The aaverage PSNR verage PSNR value value degreases by -1.6dB.degreases by -1.6dB.
A Zero-Value Prediction Technique for Fast DCT A Zero-Value Prediction Technique for Fast DCT ComputationComputation
Future workFuture work
Estimating the effect of the proposed technique on energy Estimating the effect of the proposed technique on energy consumption.consumption.
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ComparisonComparison of of the algorithmthe algorithm
Number of operationNumber of operationAverage PSNR Average PSNR
degradation (dB)degradation (dB)MaxMax MinMin AverageAverage
NormalNormal 22.9%22.9% 11.8%11.8% 14.4%14.4% -1.55-1.55
ChenChen 17.4%17.4% 7.9%7.9% 10.0%10.0% -0.94-0.94
FFTFFT 23.3%23.3% 13.6%13.6% 16.0%16.0% -2.14-2.14
The number of operations per 1block.The number of operations per 1block.
Normal : addition 1024 and multiplication 1024 times.Normal : addition 1024 and multiplication 1024 times.Chen : addition 416Chen : addition 416 and multiplication 224 times.and multiplication 224 times.FFT : addition 464FFT : addition 464 and multiplication 176 times.and multiplication 176 times.
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