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Enable a higher compression ratio in ... Bp1. MSB. 0. 1. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 1. 0. 0. 0. 1. 1. 1. 0. 1. 0. 1. 1. 7 -10. 3 -1 ... – PowerPoint PPT presentation

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Title: Aucun titre de diapositive


1
JPEG 2000
Marcela Iregui Antonin Descampe François-Olivier
Devaux
Université catholique de Louvain
2
Presentation plan
  • JPEG 2000 Features
  • Main coding blocks
  • Encoding process
  • JPEG 2000 standardization

3
Presentation plan
  • JPEG 2000 Features
  • Main coding blocks
  • Encoding process
  • Standardization process

4
JPEG 2000 Features
  • Improved compression efficiency
  • Lossy to lossless compression
  • Multiple resolution representation
  • SNR scalability
  • Progressive decoding
  • ROI coding
  • Error resilience
  • Random codestream access

5
Improved Image Quality
JPEG 1137
JPEG2000 1137
6
Improved Image Quality
JPEG 1126
JPEG2000 1126
7
Single compression / Multiple decompression
8
Progressive transmissions

Progression in quality
Compression
Storage
Progression in resolution
Spatial Progression
9
Wavelet transform
10
Wavelet transform 1
11
Wavelet transform 2
12
Wavelet transform 3

13
Multiresolution compression by wavelets


2.6 kBytes (1100)
14
Reduced Quality Reconstruction
15
Progressive Quality
1.6 download
2.2 download
8.0 download
26.4 download
100 download
16
Regions of Interest
17
Robustness to Errors
Compression 152 13.4 KB Embedded Error 16
Bytes set to zero in the middle of the files
JPEG
JPEG2000
18
Presentation plan
  • JPEG 2000 Features
  • Main coding blocks
  • Encoding process
  • Standardization process

19
Main coding blocks
Discrete Wavelet Transform (DWT)
Entropy Coding Unit (ECU)
Original image
Compressed data
20
Main coding blocks
Discrete Wavelet Transform (DWT)
Entropy Coding Unit (ECU)
Original image
Compressed data
Goal Concentrate the image information in a very
localized (and small) area ? Enable a higher
compression ratio in other areas Ouput 4
subbands with the upper left one containing low
frequencies
21
Main coding blocks
Discrete Wavelet Transform (DWT)
Entropy Coding Unit (ECU)
Original image
Compressed data
Successive decompositions are applied on the
low frequencies.
?
?
22
Main coding blocks
Discrete Wavelet Transform (DWT)
Entropy Coding Unit (ECU)
Original image
Compressed data
Each subband is then divided into code-blocks
23
Main coding blocks
Discrete Wavelet Transform (DWT)
Entropy Coding Unit (ECU)
Original image
Compressed data
  • The ECU contains two blocks
  • Context Modeling Unit (CMU)
  • Arithmetic Coding Unit (ACU)

The CMU handles first the bits bringing the
highest distortion reduction?3 groups of bits
encoded in different passes?Algorithm used
EBCOT
24
Main coding blocks
Discrete Wavelet Transform (DWT)
Entropy Coding Unit (ECU)
Original image
Compressed data
  • The ECU contains two blocks
  • Context Modeling Unit (CMU)
  • Arithmetic Coding Unit (ACU)

010011011100
  • ACU coder itself
  • Removes redundancy present in the binary
    sequence
  • Algorithm used MQ

010100
25
Presentation plan
  • JPEG 2000 Features
  • Main coding blocks
  • Encoding process
  • Standardization process

26
JPEG 2000 Overview
Image
Rate Control
Arithmetic coding
ROI
Pre- processing
Wavelet Transform
Quant.
Coefficient bit model
Data Ordering
Codestream
27
JPEG 2000 Overview
Image
Pre- processing
28
Image pre-processing
  • Tile partition (each component of each tile
    encoded
  • independently)
  • DC level shifting
  • Unsigned sample values ? Signed values
  • Colour transformation
  • To de-correlate the colour data
  • RGB ? YCbCr (ICT)
  • RGB ? YUV (RCT)

29
High resolution grid, image components and tiling
(XTsiz)
(0,0)
(ax,ay)
(YTsiz)
(bx-1, by-1)
Image Area
30
JPEG 2000 Overview
Image
ROI
Pre- processing
31
DWT
  • DWT intra-component decorrelation
  • ? concentrate image energy in a small area
  • No blocking artefacts at high compression ratios
  • Enables multi-resolution image representation

?
?
32
1-D DWT
  • Application of a pair of low-pass high-pass
    filter
  • Filter-bank charateristics symmetric,
    bi-orthogonal
  • 2 filter-banks defined in JPEG2000
  • reversible (5,3) and irreversible (9,7)

33
1-D DWT (ctd)
  • After a decomposition, most of the energy is
  • located at the low-pass output.
  • Successive applications of the filters on the
  • low-pass outputs
  • ? dyadic decomposition

34
2-D DWT
  • 2-D DWT 1-D DWT on the columns
  • followed by 1-D DWT on the rows
  • ? four filtered and subsampled images
    (subbands)
  • In JPEG 2000 5 decompositions by default

35
DWT the lifting scheme
  • Problem straightforward DWT implementation
    requires storage of the entire image in memory
  • Alternative implementation lifting scheme
  • Memory ?
  • Compute load ?
  • In-place computation
  • Principle

36
Example (5,3) filter
In general
37
Integer-to-integer transforms
  • Problem precision required on coefficients ??
    at
  • every level of the DWT
  • Solution insert quantizers in the lifting
    scheme

Quantizer truncation or rounding to the
nearest integer (still mathematically
invertible !)
38
Quantization
  • Uniform quantizer
  • Separate stepsize for each sub-band

39
JPEG 2000 Overview
Image
Pre- processing
40
Entropy coding
  • Requirements
  • embedded bit-stream
  • distortion progressive ordering
  • resolution scalability
  • localized random access to the image
  • efficient rate control
  • error resilience

41
Code-blocks and Bit-planes
  • Each sub-band of each tile component is
    partitioned
  • into code-blocks
  • Each code-block is compressed independently
    using
  • bit-plane coding

Bit-plane i
LSB
MSB
DWT
42
Arithmetic coding
  • Removes the redundancy in the encoding of the
    data
  • Assigns short code-words to more probable events
    and
  • longer code-words to the less probable
  • AC estimates the probability of the events to
    assign the
  • code-words
  • A statistical encoder must work in conjunction
    with a
  • modeller that estimates the probability of each
    possible
  • event at each point in the coding

43
Arithmetic entropy coding
Bit
Arithmetic coding
Coefficient bit model
Compressed image data
Quantified Coefficient
Context
  • The context represents the status of the
    neighbour
  • coefficients
  • The MQ-coder estimates the probability of the
    current
  • coding symbol.

44
Bit-plane coding
  • Leading all-zero bit-planes are skipped.
  • Each bit-plane is coded in three phases
  • Significance Propagation
  • Magnitude Refinement
  • Clean up

45
Significance State
  • Each coefficient in a code-block has an
    associated binary state variable called its
    significance state.
  • The significance state changes from
    insignificant to significant at the bit-plane
    where the most significant bit equal to 1 is
    found.

46
Context
  • The context is a state governed by the past
    sequence
  • of symbols

47
Bit-plane coding
  • Bit-plane blocks scan pattern
  • The first bit-plane is coded in the clean up
    pass
  • Next bit-planes are coded in three phases
  • Significance Propagation
  • Includes the coefficients that are predicted or
    most-likely to become significant and their
    sign bit as appropriated
  • Magnitude Refinement
  • Includes bits from already significant
    coefficients
  • Clean up Significance Propagation
  • Includes all the remaining coefficients

48
Bit-plane coding example
Scan Pattern for bit-plane coding
49
JPEG 2000 Overview
Image
Arithmetic coding
ROI
Pre- processing
Wavelet Transform
Quant.
Coefficient bit model
50
Compressed data
51
Distortion Estimation
Ex. Significant bit y 22 00010110 y4
24 00011000
DDDb-Da(y-0)2-(y-y4)2
20
22
23
24
25
21
1.524
0
22
24
2
8
16
32
4
1
Da
Db
Ex. Refinement bit y 22 00010110 y320
00010100
DDDb-Da(y-y4)2-(y-y3)2
20
22
23
24
25
21
1.2524
1.7524
0
22
24
20
2
8
16
32
4
1
Db
Da
52
Rate-Distortion Optimisation
truncation point ni distortion amount of data
The Image is divided in code-blocks
and
53
The optimisation principle
  • for each code-block, find the truncation points
    ni which minimise

54
Layers Abstraction
Rate-distortion optimisation (non standardised)
A layer is a quality increment for an entire
tile
55
JPEG 2000 Overview
Image
Rate Control
Arithmetic coding
Pre- processing
Wavelet Transform
Quant.
Coefficient bit model
56
Precincts and packets
Packet k Bitstream of precinct p, at resolution
r layer l, comp. c
57
Codestream syntax
Tile-body (Data)
Tile- header
Tile header
Tile- header
Main header
Tile- header
Tile-body (Data)
Tile-body (Data)

P1
P2
P3
Pn
EOC

packet header
Code-block i Entropic Data
Code-block n Entropic Data
SOP
EPH
  • Code block inclusion
  • Zero bit plane information
  • Number of coding passes
  • Data length

58
JPEG 2000 Overview
JPEG 2000 Overview
Image
Rate Control
Arithmetic coding
Pre- processing
Wavelet Transform
Quant.
Coefficient bit model
Data Ordering
Codestream
59
Region of Interest
  • Spatial random access to the codestream is
    possible by
  • tiles, precincts and code-blocks
  • A ROI mask can be created which contains the bit
    map
  • describing the coefficients that must be
    encoded
  • with better quality
  • The ROI coefficients are placed in higher
    bit-planes than
  • the background by shifting
  • The bit-planes associated
  • with the ROI are coded before
  • the background information.

60
Presentation plan
  • JPEG 2000 Features
  • Main coding blocks
  • Encoding process
  • Standardization process

61
Standardization process
  • Part 1, Core coding system
  • (intended as royalty and license-fee free)
  • Part 2, Extensions
  • (adds more features and sophistication to the
    core)
  • Part 3, Motion JPEG 2000
  • Part 4, Conformance
  • Part 5, Reference software
  • (Java and C implementations are available)
  • Part 6, Compound image file format
  • (document imaging, for pre-press and fax-like
    applications, etc.)
  • Part 7 has been abandoned

62
Standardization process
  • Part 8, JPSEC (security aspects)
  • Part 9, JPIP (interactive protocols and API)
  • Part 10, JP3D (volumetric imaging)
  • Part 11, JPWL (wireless applications)
  • Part 12, ISO Base Media File Format
  • (common with MPEG-4)

63
Open JPEG
  • Open source JPEG 2000 coder and decoder
  • Implemented in C language
  • Developped here at UCL
  • http//www.openjpeg.org/

64
References
  • ISO, JPEG 2000 International Standard
  • Taubman, D. and Marcellin, M. (November 2001)
    JPEG2000 Image compression
  • fundamentals, standards and practice, Boston,
    Kluwer Academic Publishers, 795 pgs.
  • Taubman, High performance scalable image
    processing with EBCOT, IEEE Trans. on Image
    processing, July 2000.
  • Rabbani, Joshi, An overview of the JPEG2000
    still image compression standard, Signal
    processing Image communication 17(2002) p 3-48.
  • Special issue on JPEG2000, Signal Processing
    Image Communication. Elsevier, Volume 17, Issue
    1, January 2002
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