An Overview of JPEG-2000

An Overview of JPEG-2000An Overview of JPEG-2000

Michael WMarcellin, Michael J Gormish +

, Ali Bilgin, Martin PBoliek +

University of Arizona, + Ricoh Silicon Valley

DCC 2000

AbstractAbstract

• A brief history of the JPEG-2000 standardization process

• An overview of the standard

• Some description of the capabilities provided by the standard

• Part I of the JPEG-2000 standard specifies the mini mum compliant decoder

• Part II describes optional, value-added extensions

1 Introduction1 Introduction

• Motivated by Ricoh’s submission of

the CREW (Compression with Rever

sible Embedded Wavelets) algorithm

(for JPEG-LS)• JPEG-LS — a lossless and near-lossl

ess compression

1 Introduction1 Introduction

• List of features:• State-of-the-art low bit-rate compression performa

nce• Progressive transmission by quality resolution,

component, or spatial locality• Lossy and lossless compression• Random (spatial) access to the bitstream• Pan and zoom• Compressed domain processing (eg, Rotation and

cropping)• Region of interest coding by progression• Limited memory implementations

2 The JPEG-2000 Development Process2 The JPEG-2000 Development Process

031997 WG1 meeting in Sydney– released a CDROM containing 40 test images– 00625 to 20 bits per pixel (bpp), and lossless– Wavelet/Trellis Coded Quantization (WTCQ) (submitt

ed by SAIC/UA) 031998 WG1 meeting in Geneva

– create a JPEG-2000 “Verification Model” (VM)


The WTCQ Algorithm– Basic ingredients:

The discrete wavelet transform, TCQ(Trellis Coded Quantization, Using step sizes chosen via a Lagrangian rate allocation procedure), and binary arithmetic bitplane coding

VM0 - VM2 VM3 - VM5


VM0-VM2– Supported user specified floating point and integer transfor

ms, as well as user specified decompositions(dyadic, uniform, etc)

– A fixed quantization table(“Q-table”) alternative to the Langrangian rate allocation

– scalar quantization was included in VM2– tiling, region of interest coding/decoding, error resilience, ap

proximate wavelet transforms with limited spatial support


VM0-VM2– De-interleaving of bitplanes

Significant, Refinement, Insignificant for steepest rate-distortion slopes appear first in

an embedded bitstream no inter-subband dependencies (Parallelism) change the type of progression without decodin

g– Improvements to the context modeling


VM3 - VM5– Nov 1998 WG1 meeting in Los Angeles

EBCOT (embedded block coding with optimized truncation)

– dividing each subband into rectangular blocks of coefficients and performing the bitplane coding independently on these “code-blocks”

– reduces memory requirements– included an efficient syntax for forming the sub-bitplan

e data of multiple code-blocks into “packets,” which taken together form quality “layers”


VM3 - VM5– Mar 1999 WG1 meeting in Korea

MQ-coder (submitted by Mitsubishi) adopted as the arithmetic coder for JPEG-2000

– QM-coder used in the JBIG-2

3 Final Standardization3 Final Standardization•Schedule:

• Dec 1999 “Committee Draft” (CD)• Apr 2000 “Final Committee Draft”

(FCD)• Aug 2000 “Final Draft International

Standard” (FDIS)• Dec 2000 “International Standard”

(IS)• Jul 2001 PART II

3 Final Standardization3 Final Standardization

•PART I “minimum decoder”

•PART II “extensions” , “value added”

•PART III “Motion JPEG-2000”

•PART IV JPEG-2000 compliance tests

•PART V development of free software

• JJ2000 group (Cannon France, Ericsson, EPFL) => JAVA

•UBC => C

Ricoh Silicon ValleyRicoh Silicon Valley

SAICSAIC

4 JPEG-2000 Coding Engine4 JPEG-2000 Coding Engine

Tiles and Component Transforms Partitions, Transforms, and Quantization Block Coding Packets and Layers

41 Tiles and Component Transforms41 Tiles and Component Transforms

Divide the image into rectangular, non-overlapping tiles on a regular grid– Arbitrary tile sizes are allowed – Each tile of a component must be of the same size– YCbCr, Reversible Component Transform (RCT) (allo

w lossless reconstruction of all components)

42 Partitions, Transforms, an42 Partitions, Transforms, and Quantizationd Quantization

– Transforms Given a tile, L-level dyadic(pyramidal) wavelet

transform is performed using either the floating point wavelet , or the integer wavelet(for lossless)

For more memory efficient implementations are possible using sliding window or block-based transform techniques

42 Partitions, Transforms, 42 Partitions, Transforms, and Quantizationand Quantization

– Transforms (L-level transform) “L+1” different size or resolutions lowest frequency subband(LFS) as resolution

0, also referred to as the resolution level 0 subband

j -> j+1 is referred to collectively as resolution-level j+1 subbands

42 Partitions, Transforms, 42 Partitions, Transforms, and Quantizationand Quantization

– Quantization One quantization step size is allowed per subban

d Step sizes can be chosen in a way to achieve a gi

ven level of “quality” The standard places no requirement on the metho

d used to select quantization step sizes Integer wavelet => Q=1.0, rate control through tru

ncation of embedded bitstreams– Packet partition

42 Partitions, Transforms, and 42 Partitions, Transforms, and QuantizationQuantization

– Packet partition Provided a medium-grain level of spatial localit

y in the bitstream, streaming, and (spatial) randomaccess to the bitstream

Code-blocks are obtained by dividing each packet

partition location into regular non-overlapping rectangles

an image is divided into tiles and each tile is transformed

The subbands are divided into packet partition locations

Each packet partition location is divided into code-blocks

RecapRecap

Bitplanes

Three pass– Significance– Refinement– Clean-up

All coding is done using context dependent binary arithmetic coding

Block CodingBlock Coding

1st MSB 2ed MSB Least MSB

Block CodingBlock Coding

• For brevity, JPEG-2000 uses no more than nine contexts to code any given type of bit (ie, significance, refinement, etc)

Packets and LayersPackets and Layers

• A Packet can be interpreted as one quality increment for one resolution level at one spatial location

• A Layer can be interpreted as one quality increment for the entire

• image at full resolution• current VM supports approximately

50 layers

5 JPEG-2000 Bitstream5 JPEG-2000 Bitstream

Provides better rate-distortion performance, for any given rate, then the original JPEG

Progression can be changed, additional quantization can be done, or a server can respond only with the data desired by a client, all without decoding the bitstream


Progression– resolution, quality, spatial location, and compo

nent– Achieved by the ordering of packets within the

bitstream– Progression type can be changed at various pl

aces within the bitstream– Allows an icon to be displayed first, then a scre

en resolution image


Parsing– a parser can read all the markers, change the type

of progression in the markers, write the lengths of the packets out in the new order, and write the packets themselves out in the new order

– When sending a color image to a grayscale printer, there is no point in sending color information

– Fifty layers are provided


Spatial Accessibility– “Parsing” from one file to another file– Regions of interest (ROI)– All of the code-blocks which contain coeffic

ients affecting the ROI can be identified, and the bitplanes of those coefficients can be stored in higher layers relative to other coefficients


Image Editing and Compression– Allow uncompressed tiled image formats allow re

gions of and image to be edited, and only those tiles affected need to be rewritten to disk

– PART I allow 90,180, and 270 degree rotations, and horizontal and vertical flips of an image

– PART II flagged in the bitstream, and left for the decoder to perform

6 Performance6 Performance

2048 by 2560

6 Performance6 Performance

7 Conclusion7 Conclusion

• ISO sells copies of the specification but only after the “International Standard” stage is reached

• JPEG-2000 is unlikely to replace JPEG in low complexity applications at bitrates in the range where JPEG performs well

• For applications requiring either higher quality or lower bitrates, or any of the features provided, JPEG-2000 should be a welcome standard

Coding principlesCoding principles

Data orderingData ordering

Annex B Data ordering– B.1 Image division into components– B.2 Image division into tiles and tile-components– B.4 Tile-component division into resolutions and sub-

bands– B.5 Division of resolutions into precincts– B.6 Division of the sub-bands into code-blocks– B.7 Layers

– B.8 Packets

– B.9 Packet header information coding

– B.10 Tile Data and Tile-Parts– B.11 Progression Order.

Image division into Image division into componentscomponents

Image division into tiles and tile-Image division into tiles and tile-componentscomponents

B4, B5, B6B4, B5, B6

B7, B8, B9, B10B7, B8, B9, B10

– B7 Layers

– B8 Packets

– B9 Packet header information coding

– B10 Tile Data and Tile-Parts

Progression OrderProgression Order

Annex C Arithmetic entropy Annex C Arithmetic entropy codingcoding

C.1 Binary encoding (informative)

C.2 Description of the arithmetic encoder (informative)

C.3 Arithmetic decoding procedure

Annex D Coefficient bit Annex D Coefficient bit modelingmodeling

D.1 Code-block scan pattern within code-blocks

D.2 Coefficient bits and significance D.3 Decoding passes over the bit-planes D.4 Initializing and terminating D.5 Error resilience segmentation symbol D.6 Selective arithmetic decoding bypass D.7 Vertically causal context formation D.8 Flow diagram of the code-block

coding


D.1 Code-block scan pattern within code-blocks


D.3 Decoding passes over the bit-planes– Significance propagation decoding pass– Magnitude refinement pass– Cleanup pass

Annex E QuantizatioAnnex E Quantizationn

E.1 Scalar coefficient dequantization (normative)

E.2 Scalar coefficient quantization (informative)

Annex E QuantizatioAnnex E Quantizationn

Annex F Discrete wavelet Annex F Discrete wavelet transformation of tile transformation of tile componentscomponents

F.1 Introduction and overview

F.2 The inverse discrete wavelet transformation (normative)

F.3 Forward Transformation (informative)

Annex F Discrete wavelet Annex F Discrete wavelet transformation of tile transformation of tile componentscomponents

Annex G DC level shifting Annex G DC level shifting and component and component transformationstransformations

G.1 DC level shifting of tile components

G.2 Reversible component transformation (RCT)

G.3 Irreversible component transformation (ICT

G.4 Chrominance component sub-sampling and the image reference grid (informative)

Annex G DC level shifting Annex G DC level shifting and component and component transformationstransformations

Annex H Coding of Annex H Coding of images with Regions images with Regions of Interestof Interest

An ROI is a part of an image that is coded earlier in the codestream than the rest of the image (the background).

The coding is also done in such a way that the information associated with the ROI precedes the information associated with the background.

The method used (and described in this annex) is the Maxshift method.


H.1 Description of the Maxshift method H.2 Region of interest mask generation H.3 Remarks on Region of Interest coding

H.4 An example of the interpretation of the Maxshift method (Informative)


H.1 Description of the Maxshift method – Generate ROI mask, M(x,y) (Annex H.2).– Find the scaling value, s (Annex H.1.2).– Scale down all background coefficients

given by M(x,y) using the scaling value, s (Annex H.2).

– Write the scaling value, s, into codestream using the RGN marker (Annex A.6.3).

其他的其他的 AnnexAnnex

Annex A Codestream syntax Annex I JP2 file format syntax Annex J Examples and Guidelin

es Annex K Bibliography Annex L Patent Statement

DEMO - Gray level DEMO - Gray level bike-d_0.25 512x512 0.25

DEMO - Gray levelDEMO - Gray levelbike-d_0.5 512x512 0.5

DEMO - Gray levelDEMO - Gray levelbike-d_1 512x512 1.0

DEMO - ColorDEMO - Colorbike-d-c_0.25 512x512 0.25

DEMO - ColorDEMO - Colorbike-d-c_0.5 512x512 0.5

DEMO - ColorDEMO - Colorbike-d-c_1 512x512 1.0

An Overview of JPEG-2000

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