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JPEG Still Image Data Compression Standard. JPEG Introduction - The background. JPEG stands for Joint Photographic Expert Group A standard image compression method is needed to enable interoperability of equipment from different manufacturer

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Presentation Transcript
jpeg introduction the background
JPEG Introduction - The background
  • JPEG stands for Joint Photographic Expert Group
  • A standard image compression method is needed to enable interoperability of equipment from different manufacturer
  • It is the first international digital image compression standard for continuous-tone images (grayscale or color)
  • Why compression is needed?
    • Ex) VGA(640x480)  640x480x8x3=7,372,800bits

with compression  200,000bits without any visual degradation

jpeg introduction what s the objective
JPEG Introduction – what’s the objective?
  • “very good” or “excellent” compression rate, reconstructed image quality, transmission rate
  • be applicable to practically any kind of continuous-tone digital source image
  • good complexity
  • have the following modes of operations:
    • sequential encoding
    • Progressive encoding
    • lossless encoding
jpeg overview



image data


image data











coding tables

The basic parts of an JPEG encoder

JPEG Overview
jpeg baseline system1





88 blocks

DCT-based encoder


image data



image data





The basic architecture of JPEG Baseline system

JPEG Baseline System

JPEG Baseline system is composed of:

  • Sequential DCT-based mode
  • Huffman coding
JPEG Baseline System

– Why does it work?

Frequency sensitivity of Human Visual System

  • Lossy encoding
  • HVS is generally more sensitive to low frequencies
  • Natural images
the baseline system dct
The mathematical representation of FDCT (2-D):


f(x,y): 2-D sample value

F(u,v): 2-D DCT coefficient

The Baseline System – DCT
  • The Discrete Cosine Transform (DCT) separates the frequencies contained in an image.
  • The original data could be reconstructed by Inverse DCT.
the baseline system dct cont
An example of 1-D DCT decomposition

Before DCT (image data)

After DCT (coefficients)

The 8 basic functions for 1-D DCT

The Baseline System-DCT (cont.)
the baseline system dct cont1
The Baseline System-DCT (cont.)
  • The DCT coefficient values can be regarded as the relative amounts of the 2-D spatial frequencies contained in the 88 block
  • the upper-left corner coefficient is called the DC coefficient, which is a measure of the average of the energy of the block
  • Other coefficients are called AC coefficients, coefficients correspond to high frequencies tend to be zero or near zero for most natural images
the baseline system quantization
The Baseline System – Quantization
  • Why quantization? .
    • to achieve further compression by representing DCT coefficients with no greater precision than is necessary to achieve the desired image quality
  • Generally, the “high frequency coefficients” has larger quantization values
  • Quantization makes most coefficients to be zero, it makes the compression system efficient, but it’s the main source that make the system “lossy”

F(u,v): original DCT coefficient

F’(u,v): DCT coefficient after quantization

Q(u,v): quantization value

the baseline system quantization cont
The Baseline System-Quantization (cont.)

JPEG Luminance quantization table

a simple example
Original image pattern

After FDCT(DCT coefficients)

Digitized image

A simple example
a simple example cont
A simple example(cont.)

DCT coefficients

Quantized coefficients

baseline system dc coefficient coding
DC difference

quantized DC



Differential pulse code modulation

Baseline System - DC coefficient coding
  • Since most image samples have correlation and DC coefficient is a measure of the average value of a 88 block, we make use of the “correlation” of DC coefficients
baseline system ac coefficient coding
Horizontal frequency

Vertical frequency

Baseline System - AC coefficient coding
  • AC coefficients are arranged into a zig-zag sequence:
  • 3 0 0 -3 0 -3 0 0 0 0

-1 0 -2(EOB)

baseline system statistical modeling
Baseline System - Statistical modeling
  • Statistical modeling translate the inputs to a sequence of “symbols” for Huffman coding to use
  • Statistical modeling on DC coefficients:
    • symbol 1: different size (SSSS)
    • symbol 2: amplitude of difference (additional bits)
  • Statistical modeling on AC coefficients:
    • symbol 1: RUN-SIZE=16*RRRR+SSSS
    • symbol 2: amplitude of difference (additional bits)
Additional bits for sign and magnitude

Huffman AC statistical model

run-length/amplitude combinations

Huffman coding of AC coefficients

jpeg 2000
JPEG 2000
  • Allow efficient lossy and lossless compression within a single unified coding framework
  • Progressive transmission by quality, resolution, component, or spatial locality
  • Compressed domain processing
  • Region of Interest coding
  • JPEG2000 is NOT an extension of JPEG
    • Wavelet Transform
    • An extremely flexible bitstream structure
jpeg2000 roi coding
JPEG2000 ROI coding
  • Bit plane shift
  • Finer Quantization level used