Filters in Image Processing
Image Compression Standards
David Svoboda
email: svoboda@fi.muni.cz
Centre for Biomedical Image Analysis
Faculty of Informatics, Masaryk University, Brno, CZ
November 8, 2019
David Svoboda (CBIA@FI) Filters in Image Processing autumn 2019 1 / 30
Outline
1 Introduction
2 CCITT – Group 3 & 4
3 JPEG
4 JPEG2000 (J2K)
5 MPEG
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1 Introduction
2 CCITT – Group 3 & 4
3 JPEG
4 JPEG2000 (J2K)
5 MPEG
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Image Compression Standards
Binary image compression
CCITT Group 3 & 4 – run length encoding
(Consultative Comittee of the International Telephone and Telegraphy)
JBIG – arithmetic compression
(Joint Bilevel Imaging Group)
Continuous tones still image compression standards
JPEG – discrete cosine transform
(Joint Photographics Experts Group)
JPEG 2000 – discrete wavelet transform
Video compression standards
MPEG-1, MPEG-2 – DCT and predictive coding
(Moving Pictures Experts Group)
MPEG-4 – Wavelet based coding
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1 Introduction
2 CCITT – Group 3 & 4
3 JPEG
4 JPEG2000 (J2K)
5 MPEG
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CCITT Group 3 1D
Specification
Proposed for fax machines (black-and-white bitmaps).
For encoding a combination of Huffman and RLE is used.
Often called Modified Huffman coding.
Trained on eight documents:
typed business letter (English)
circuit diagram (hand drawn)
printed and typed invoice (French)
densely types report (French)
printed technical article including figures and equations (French)
graph with printed captions (French)
dense document (Kanji)
handwritten memo with very large white-on-black letters (English)
Code words for lengths 1–2560 pixels are stored in publicly known
table.
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CCITT Group 3 1D
Specification
Part of table with CCITT Group 3 codes
run length white code word black code word
0 00110101 0000110111
1 000111 010
2 0111 11
3 1000 10
4 1011 011
5 1100 0011
6 1110 0010
7 1111 00011
...
...
...
1344 011011010 0000001010011
1408 011011011 0000001010100
1472 010011000 0000001010101
...
...
...
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CCITT Group 3 1D
Specification
The documents are scanned line by line.
Termination codes . . . Short run lengths (1–63 pixels)
Make-up codes . . . Long run lengths (64 and more pixels)
Each run length (white/black) is split into sequence of code words
Some examples:
12 white pixels → 001000
76 white pixels (=64+12) → 11011|001000
2561 black pixels (=2560+1) → 000000011111|010
8800 black pixels (=2560+2560+2560+1088+32) →
00000001111|000000011111|000000011111|0000011110101|0000011010
Each line end is encoded with a special EOL code word:
000000000001
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CCITT Group 3 2D
Specification
2-dimensional coding
Images are divided into several groups of K lines.
K is typically 2 or 4.
The first line of each group is encoded using CCITT Group 3 1D
method.
The rest of lines is encoded using a differential scheme where new code
words specific for 2D encoding are introduced.
Typical compression ratio 1 : 10 ∼ 1 : 20
Pay attention to error propagation!
The ”K-factor” allows more error-free transmission
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CCITT Group 4 2D
Specification
Designed for encoding data on disk drives → no built-in transition
error detection/correction.
No EOL codes (not needed).
K set to infinity.
Use of CCITT G3 & G4
TIFF compression Type 2 . . . G3 1D
TIFF compression Type 3 . . . G3 2D
TIFF compression Type 4 . . . G4 2D
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1 Introduction
2 CCITT – Group 3 & 4
3 JPEG
4 JPEG2000 (J2K)
5 MPEG
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JPEG
What does JPEG mean?
JPEG = Joint Photographic Experts Group
The popular image file format is ”JPEG File Interchange Format
(JFIF)”
The aims of JPEG:
storage of continuous tone grayscale and color images
recognizable image at 0.083 bit/pixel
useful image at 0.25 bit/pixel
feasibility of 64 kbit/s (ISDN)
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JPEG
1 color component transform 8-bit RGB → YCrCb
(Y is the luminance component and Cb and Cr are the blue and red
chrominance components)


Y
Cb
Cr

 =


0.299 0.587 0.114
−0.169 −0.331 0.500
0.500 −0.419 −0.081




R
G
B


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JPEG
2 reduce resolution of Cr and Cb by factor 2
3 process Y, Cr and Cb independently
4 split the image into 8 × 8 blocks
5 apply 8 × 8 forward DCT on each block
6 quantization using zonal thresholding
(left – luminance table; right – chrominance table)
16 11 10 16 24 40 51 61 17 18 24 47 99 99 99 99
12 12 14 19 26 58 60 55 18 21 26 66 99 99 99 99
14 13 16 24 40 57 69 56 24 26 56 99 99 99 99 99
14 17 22 29 51 87 80 62 47 66 99 99 99 99 99 99
18 22 37 56 68 109 103 77 99 99 99 99 99 99 99 99
24 35 55 64 81 104 113 92 99 99 99 99 99 99 99 99
49 64 78 87 103 121 120 101 99 99 99 99 99 99 99 99
72 92 95 98 112 100 103 99 99 99 99 99 99 99 99 99
7 compression quality is driven by Q-scale factor (1–100%) that
multiplies the items from the tables given above
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JPEG
8 apply lossless predictive coding to quantized DC (lowest frequency)
coefficients from DCT
9 read remaining quantized values from DCT in zigzag patternStoring DCT coeffi
0 1
2
3
4
5 6
7
8
9
10
11
12
13
14 15
16
17
18
19
20
21
22
23
24
25
26
27 28
29
30
31
32
33
34
35 36
37
38
39
40
41
42
43
44
45
46
47
48 49
50
51
52
53
54
55
56
57 58
59
60
61
6362
horizontal frequency
verticalfrequency
10 locate sequences of zero coefficients and use RLE
11 apply Huffman/arithmetic coding on zero run-lengths and magnitude
of AC values
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1 Introduction
2 CCITT – Group 3 & 4
3 JPEG
4 JPEG2000 (J2K)
5 MPEG
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JPEG 2000
Preprocessing
1 cut the image into tiles of size greater than [128×128] to prevent
blocking artifacts but enabling ROI selection
2 DC level shift for channel of s bit depth:
[0, 2s
− 1] → [−2s−1
, 2s−1
− 1]
3 color transform: RGB → YCrCb
irreversible component transform (lossy):


Y
Cb
Cr

 =


0.299 0.587 0.114
−0.169 −0.331 0.500
0.500 −0.419 −0.081




R
G
B


reversible component transform (lossless):
Y =
R + 2G + B
4
Cr = B − G
Cb = R − G
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JPEG 2000
Forward transform
4 apply DWT via lifting scheme to each tile independently
Daubechies 9/7 filter (floating-point wavelet – lossy):
LoD = [0.027 -0.017 -0.078 0.267 0.603 0.267 -0.078 -0.017 0.027]
HiD = [0.046 -0.029 -0.296 0.558 -0.296 -0.029 0.046]
Le Gall 5/3 filter (integer wavelet – lossless):
LoD = [-0.125 0.25 0.75 0.25 -0.125]
HiD = [-0.25 0.5 -0.25]
5 level of detail of DWT is a parameter of compression
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JPEG 2000
Quantization
6 quantize DWT coefficients for each subband b individually:
qb(x, y) = sign(Ib(x, y))
|Ib(x, y)|
∆b
Ib . . . original intensity values in the processed subband b
qb . . . matrix with quantized values
∆b . . . quantization step b (for lossless compression ∆b = 1)
low frequency subband
high frequency subbands
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JPEG 2000
Precincts and code-blocks
subband
precinct
code−block
7 divide individual DWT
subbands into rectangular
blocks called precincts
8 each precinct is further
divided into non-overlapping
rectangles called code-blocks
Notice: Each code-block forms
the input to entropy encoder and
is encoded independently
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JPEG 2000
Entropy coding
9 the coefficients in a code block are separated into bitplanes and read
in the order from MSB to LSB (sign bit is the second one)
10 the sequence of bit is coded using arithmetic encoder
(probability of each symbol is adaptively derived from its neighbours)
15 6
−3 −11
15
6
−11
sign MSB LSB
0
0
1
1
1
0
0
1
1
1
0
0
1
1
1
1
1
0
1
1
coding scan
arithmetic coder
−3
code−block
bit stream
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JPEG 2000
Properties
an image is partitioned into:
tiles – precincts – code-blocks ↔ coarse – medium – fine
memory efficient implementations
streaming
easy direct access to specified positions
simple modifications (rotation, crop, . . . ) of an image do not require
decompression of an image
reading of ROIs instead of decompressing the whole images
progressive access
elimination of blocking artifacts typical for JPEG
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JPEG 2000
Comparison
original (979 kB) JPEG (6.21 kB) JPEG2000 (1.83 kB)
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1 Introduction
2 CCITT – Group 3 & 4
3 JPEG
4 JPEG2000 (J2K)
5 MPEG
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MPEG
Basic principle
I-frames . . . intraframe/independent frame
frame encoded using JPEG-like compression scheme
(in MPEG-1 & MPEG-2)
P-frames . . . predictive frame
the difference (measure of correlation) to a previous P- or I-frame;
variable length coded
B-frames . . . bidirectional frame (the most common frames)
difference between the current frame and a prediction of it based on
the previous I- or P-frame and the next P-frame
→ when movement of an object gradually uncovers a background area
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MPEG
Basic principle
Display order of frames:
I B B B P B B B P B B B P
time
Coding order:
I B B B B B BP P B P B
time
B
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MPEG
Motion compensation
Motion Vector
(∆x , ∆y ) = (blockn+1
x − blockn
x , blockn+1
y − blockn
y )
Notice: Correct detection of motion vector influences the compression quality.
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MPEG
Motion compensation (an example)
Original frame
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MPEG
Motion compensation (an example)
Difference between original and the next frame
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MPEG
Motion compensation (an example)
Difference between original and the next frame shifted by 2 pixels to the right
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Bibliography
Salomon, D. Data Compression, The Complete Reference, 4th
edition, Springer, London, 2007, ISBN-1846286025
Gonzalez, R. C., Woods, R. E. Digital image processing / 2nd ed.,
Upper Saddle River: Prentice Hall, 2002, pages 793, ISBN
0201180758
Rabbani, M., Joshi R. An overview of the JPEG 2000 still image
compression standard, Signal Processing: Image Communication,
Volume 17, Issue 1, January 2002, Pages 3-48, ISSN 0923-5965
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You should know the answers . . .
Why do we convert RGB into YCrCb in JPEG and JPEG2000
standard?
Explain the meaning of luminance/chrominance table.
Explain the origin of the phenomenon called blocking artifact.
How and why do we use predictive coding in JPEG standard?
Describe the frame ordering in MPEG scheme.
What is a difference between I, P, and B frames?
How do we loose the information when using JPEG/JPEG2000?
Encode the sequence [101010101010] using CCITT G3 1D scheme.
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