1. JPEG Image Coding Standard
Jianping Fan
Department of Computer Science
University of North Carolina at Charlotte
Charlotte, NC 28223

2. 1. What’s meaning of JPEG?
JPEG: Joint Photographic Experts Group
2. Why we need JPEG?
a. Save our money for storage and transmission
b. Good tradeoff between image quality and compression ratio
c. Easy for VLSI chip design and software design
d. Reasonable computation complexity
e. Useful for most image source

3. 3. Color Space for Image Representation
RGB: (red, green, & blue) for image display R
white
black
R=G=B G B
Any color can be represented as a combination of R, G, B!

4. 3. Color Space for Image Representation

5. 3. Color Space for Image Representation
How to generate and display an image?
Red sensor
amplifier
scene
green sensor
lens
amplifier
Blue sensor
amplifier

6. 3. Color Space for Image Representation

7. 4. Color Space for Image Coding
RGB space is good for image display but not good for image coding because the separation of colors is not so efficient!
YUV space:
Y: luminance component (gray level version of the image)
U & V: chrominance components (give the information
to convert a gray level image to color image).
Y = 0.299R G B
U = 0.564(B-Y)
V = 0.713(B-Y)

8. 5. Color Space for Human Vision System
Color spaces for image processing
HSV:
H: Hue
S: Saturation
V: Value

9. 6. Image Quality
Image resolution is related to the quality of image (fine details),
storage size, ….
Software MPEG 120*160
Workstation: 900*1152
Advanced TV: 720*1280
SIF image: *320
HDTV: *1920
VGA: *640
XGA: *768
VGA: video graphics array
PC monitor: *800

10. 7. JPEG Encoder
JPEG encoder
…..
1:80
Compressed image size
Original image size
352*288*8 + 2*176*144*8
= bits
15206 bits
Spatial correlations among neighboring pixels

11. 7. JPEG Encoder
Why we can reduce the bit rate?
How we can reduce the bit rate? Or
Why images can be compressed?
How can we compress images?

12. How to exploit such spatial similarity or redundancy?
7. JPEG Encoder
Spatial similarity or
redundancy between
the pixels
How to exploit such spatial
similarity or redundancy?

13. 7. JPEG Encoder
How to exploit such spatial similarity or redundancy? ---- Data Transformation
Energy Concentration
DCT

14. 7. JPEG Encoder JPEG Encoder Entropy encoder DCT 100111000…….. table
Compressed image data stream
Entropy
encoder
DCT
quantizer
……..
table
table
Reconstructed image
JPEG Decoder
Compressed image data stream
Entropy
decoder
Dequantizer
IDCT
……..
IDCT: inverse DCT
table
table

15. 8. How to realize JPEG Encoder?
a. Image partition for coding:
Macroblock Y
block
DCT U V
Entropy coding
…………

16. Why uses 8x8 blocks? 8. How to realize JPEG Encoder?
a. Image partition for coding:
Macroblock Y
block
DCT U V
Why uses 8x8 blocks?
Entropy coding

17. 8. How to realize JPEG Encoder?
b. DCT (Discrete Cosine Transformation):
DCT
Why DCT is helpful?

18. 8. How to realize JPEG Encoder?
c. Why we use DCT?
DC Coefficient: average image component
AC Coefficients: variance between original image and average 8
low
Most energy of an image may concentrate on the low-frequency region!
high
What we can gain from this property? 8

19. 8. How to realize JPEG Encoder?
d. Quantization
Fq(u,v) = Round {F(u,v)/Q(u,v)}
Q(u,v) is defined by:
Scale*q(u,v)
q(u,v) is a table as: u 8 v 50

20. 8. How to realize JPEG Encoder?
e. Why we use quantization?
If 16<x<32,
[x] = 24;
Just use one value!
Quantization reduces the amplitude of the coefficients which contribute little or nothing to the quality of image!
More zero high frequency coefficients!

21. 8. How to realize JPEG Encoder?
f. Zigzag scan
Zigzag
DCT
Run-length code
Quantization
(5,0), (2,0), (2,0), (3,4), (1,4), (1,41)
Recall: what we can gain from this?

22. 8. How to realize JPEG Encoder?

23. 8. How to realize JPEG Encoder?
g. Coding of DC Coefficient:
DC(i,j) = DCi - DCj
DCi
DCj
Adjacent blocks may have similar average intensities!
DC(i,j) is small!

24. 8. How to realize JPEG Encoder?
h. Entropy Coding (table searching)
Table & Table searching for DC coding:
DC difference 3
100
Huffman codes 2 10 1
skip -1 1 -2 11 -3
101
Can you image the maximum value for DC?
What you find from this table?

25. 8. How to realize JPEG Encoder?
h. Entropy Coding (table searching)
Table & Table searching for AC coding:
s: 0 for positive; 1 for negative.
(run, length)
code
(run, length)
code
(30,1) s
(0,1) 1s
(0,2)
0100s
How to design more efficient Huffman table searching technique?

26. 9.
Quality vs. Compression Ratio
GIF
JPEG
1:20

27. 9. Quality vs. Compression Ratio
original
1:8
1:50
1:15

28. 10. Why not use large size blocks?
Why not take whole image
as a coding block?
Why we can achieve
image compression?

29. 11. JPEG2000 & Hierarchical Coding
Question: what kind of image can be compressed efficiently?
a.wavelet transform
b.scalable coding

30. 11. JPEG2000 & Hierarchical Coding