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April 30th, 2003. Parallel Design of JPEG2000 Image Compression. Xiuzhen Huang. CS Department UC Santa Barbara. Outline. Introduction to image compression JPEG2000 compression scheme Parallel implementation of JPEG2000 On distributed-memory multiprocessors - PowerPoint PPT Presentation
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Page 1CS Department
Parallel Design of JPEG2000 Image Compression
Xiuzhen Huang
CS DepartmentUC Santa Barbara
April 30th, 2003
Page 2CS Department
Outline
• Introduction to image compression• JPEG2000 compression scheme• Parallel implementation of JPEG2000
– On distributed-memory multiprocessors– On shared-memory multiprocessors
• Conclusion
Page 3CS Department
Introduction to Image Compression
Why do we need image compression?
1280 pixels
800 pixels
1280 800 3 (RGB)= 3 M bytes
File size of a small digital photo without compression:
To speedup the image transmission over Internetand reduce image storage space, we need compression
Page 4CS Department
Introduction to Image Compression
Original Picture3 M bytes
JPEG2000 Compression19 K bytes
• Compression Ratio: >150 times !• No noticeable difference in picture quality
Page 5CS Department
JPEG2000 International Standard
JPEG2000: the new international standard for image compression, is much more efficient than the old JPEG international standard.For the same compression ratio / bit rate / file size, the JPEG2000 picturehas much better quality.
JPEG JPEG2000Original Picture
Compression ratio : 50:1
Strong blockiness
Page 6CS Department
JPEG2000 International Standard
JPEG2000 has a much Higher computational complexity than JPEG,especially for larger pictures.
Need parallelimplementation to reduce compressiontime.
Page 7CS Department
JPEG2000 Compression Scheme
WaveletTransform
Input BlockwisePartition
Codingof each block
BinaryCompressed data
Major steps of JPEG2000 image compression
• Wavelet transform uses most of the image compression time (>80%)• parallel implementation should focus on wavelet transform
Page 8CS Department
JPEG2000 Compression Scheme
Brief Introduction to Wavelet Transform
Step 1: Horizontal wavelet transform of an image
for each rowdo 1-D wavelet transform;
end
What is 1-D wavelet transform ?
Page 9CS Department
A simple example: 1-D Haar wavelet transform
One array of image data
[1, 1]
[1, -1]
2
2
First half of the output
Second half of the output
JPEG2000 Compression Scheme
HorizontalWavelet
Transformof Each Row
Averageof neighboringpixels
Differenceof neighboringpixels
Low-Frequencycoefficients
High-Frequencycoefficients
Low High
Low-pass filter
high-pass filter
Down-sample by 2
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JPEG2000 Compression Scheme
Wavelet Transform
Step 2: Vertical transform of image
for each column of the new imagedo 1-D wavelet transform;
end
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HorizontalWavelet
Transformof Each Row
Low High
VerticalWavelet
Transform of Each Column
LowLow
HighLow
LowHigh
HighHigh
JPEG2000 Compression Scheme
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Parallel Design of JPEG2000 Compression
Two Parallel Computing Architectures
Shared-Memory Multiprocessors
• Has a single address space. • Allow processors to communicate through variables stored in a
shared address space• Programming tool: openMP
Distributed-Memory Multiprocessors
• Each processor has its own memory module
• Processors communicate to each other over a high-speed network
• Programming tool: MPI (Message Passing Interface)
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Parallel Implementation of JPEG2000 Compressionon Distributed-Memory Multiprocessors
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Parallel Design of JPEG2000 Compression-DMP
Traditional Approach
• The image is first divided into n regions on rows.
• Each processor performs 1-D horizontal wavelet transform
• Then, the new image is divided into n regions on columns.
• Each processor performs 1-D vertical wavelet transform.This approach requires intensive data transmission among processors, has very high network communication cost.
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Parallel Design of JPEG2000 Compression-DMP
Tiling Approach
• JPEG2000 international standard supports tile-based image compression.
• A large image is divided into several tiles and each image tile is compressed independently.
P1 P2 P3
P5
P8P7
P4 P6
P9
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Choose MPI for parallel implementation of JPEG2000, because the JPEG2000 software is written in C, which supported by MPI. Basic framework is:
Parallel Design of JPEG2000 Compression-DMP
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Number of processors
Com
pres
sion
Tim
e (S
ec)
The picture shows the compression time using different tile size.For each tile size,processor number increases,compression time is reduced.The small tile need larger computation overhead.
Size: 32
Size: 256
Image:512x512
Parallel Design of JPEG2000 Compression-DMP
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• There is a jump between one process and two processes.
• When there is only one process, JPEG2000 compression is sequential
• If there are more than two processes involved in the program, Process 1 is responsible for collecting data, while the others are responsible for processing different tiles and sending processed data back to the Process 1.
Note
Parallel Design of JPEG2000 Compression-DMP
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Parallel Implementation of JPEG2000 Compressionon Shared-Memory Multiprocessors
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Parallel Design of JPEG2000 Compression-SMP
A problem with tile-based approach
Images compressed by JPEG, JPEG2000, and JPEG2000 with relatively small tiles.
Each tile is compressed independently, which causes discontinuity across tile edges, also called blockiness.
Page 21
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Parallel Design of JPEG2000 Compression-SMP
• Another parallel architecture is shared-memory multiprocessors.
• The excellent price-performance ratio of Intel-based SMPs make such systems very popular in many data processing applications.
• There are also many available programming tools for shared memory processor, such as openMP and Java Threads.
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• In SMP, we do not need worry about data communication over network, because the data is in the shared memory. So there is no need for tile partitioning.
• Therefore, we can use the traditional data partitioning approach for horizontal and vertical wavelet transforms.
Parallel Design of JPEG2000 Compression-SMP
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Parallel Design of JPEG2000 Compression-SMP
• JPEG2000 image compression is implemented on a 4-processor SMP system using direct openMP.
• The speedup in wavelet transform is only about 1.6 times, which is supposed to be near 4 times.
• Why?
Page 24
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Parallel Design of JPEG2000 Compression-SMP
It is found that the vertical wavelet transform requires more than 10 times the horizontal transform.
But we know that both vertical and horizontal transforms have the same number of operations.
vertical horizontal
Page 25
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Cache Miss Problem
Parallel Design of JPEG2000 Compression-SMP
• In computer memory, the image data is stored line by line in a raster-scan order (from left to right, from top to bottom).
• Each continuous block of image data is brought into the cache from memory for wavelet transform.
• In horizontal wavelet transform, as the filter window is moving, the data of next transform is often available, few cache miss.
Page 26
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Cache Miss Problem
Parallel Design of JPEG2000 Compression-SMP
• In vertical wavelet transform, the filtering is done in the vertical direction, however, the data is brought into cache in a horizontal way. So, there are very frequent cache miss.
data
filt
erin
g
Solution
Do vertical transform of several columns at the same time to make full use of the existing data in the cache. , instead of column by column Significantly reduces cache miss.
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Original Verticaltransform
Parallel Design of JPEG2000 Compression-SMP
Improved Verticaltransform
The vertical transform is speed upby about 10 times.
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Parallel Design of JPEG2000 Compression-SMP
Using the improved vertical wavelet transform, the overall speedup times of wavelet transform is now close to the number of processors.
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• Give a brief review JPEG2000 image compression.
• Discussed two approaches for parallel implementation of JPEG2000 image compression: distributed memory multiprocessor and shared memory multiprocessor.
Conclusion
Question?