IMAGE COMPRESSION
Image Compression
• Why?
• Reducing transportation times
• Reducing file size
• A two way event - compression and decompression
Compression categories
• Compression = Image coding
• Still-image compression
• Compression of moving image
INTERFRAME and INTRAFRAME
PROCESSING
Interframe Processing
Point to Point
Predictive Encoding
Line to Line
Intraframe
Processing
Image compression meters
• Compress ratio =
Original image size
Compressed image size
• The larger the compression ratio, the smaller the result
image
Image compression
• Compression method is not same as the image file-
interchange format.
• Example TIFF -file format supports several compression methods
Why Can We Compress?
• Spatial redundancy
• Neighboring pixels are not independent but correlated
• Temporal redundancy
Information vs Data
REDUNDANT
DATA
INFORMATION
DATA = INFORMATION + REDUNDANT DATA
Image compression fundamentals
• Same compression method is not to be used more than
once.
• But you can use different methods at the same time,
especially different lossless methods like LZW and PKZIP
Image compression: symmetry
Color image compression
• RGB - apply the same compression scheme to the
three color component images
• Convert the image from the RGB color space to a less
redundant space, because RGB components carries a
lot of same information.
• RGB --> HSB, when Hue and Saturation components
are well compressed
Color image
compression
RED
GREEN
BLUE
BRIGHTNESS
SATURATION
H
U
E
Lossless image compression
• Image can be decompressed back to original
• Used when image’s future purpose of use is not known,
example space exploration imagery is often studied for
years following its origination
Run-Length Coding
y
78| 1
76| 5
x
76
76
76
76
Run-Length Codes
(Brightness | Run-length)
76
78
79| 2
79
79
80| 3
80
80
98| 2
80 98
98
Run-length coding
• Codes the nearby pixels which has same brightness
values in two values - Run-Length, RLE and brightness
value
• Error sensitive
• Data explosion
• Data errors
Huffman or Entropy Coding

Converting the pixel brightness values in the original
image to new variable-length codes, based on their
frequency of occurrence in the image
Brightness
Histogram
Raw Image
Data
98,100,103,
87,86,95...
Arrange values
in descending
frequency of
occurrence
Assign Huffman
variable-length
codes
Huffman Code
Image Data
Substitute
Huffman
codes
The flow of the Huffman coding operation.
Append
code
list
0,10,0,1100
1111,11011
Lossless or Lossy Compression
• Lossless compression
• There is no information loss, and the image can be
reconstructed exactly the same as the original
• Applications: Medical imagery, Archiving
• Lossy compression
• Information loss is tolerable
• Many-to-1 mapping in compression eg. quantization
• Applications: commercial distribution (DVD) and rate
constrained environment where lossless methods
can not provide enough compression ratio
Predictive Coding
• Based on the assumption that pixel’s brightness can
be predicted based on the brightness of the preceding
pixel
• Codes only the brightness value of the pixel next to
each other
• DPCM (Differential Pulse Code Modulation)
DPCM (Differential Pulse Code
Modulation)
Block Coding
• Searching for repeated patterns (mostly in rows)
• Pixel patterns are put in Codebook
• Original image’s pixel pattern is replaced by codebook
index in compressed image
Block Coding
• LZW- compression (Lempel-Ziv-Welch)
• Compression ratio 2:1 - 3:1
• Starting with a 256 single-pixel long codebook ->
adding until it reaches its maximum length
• LZW+Huffmann, where most common pixel patterns
get shortest codes
TRANSFORM CODING
• Transform Coding
- transform image
- code the coefficients of the transform
- transmit them
- reconstruct by inverse transform
• Benefits
- transform coeff. relatively uncorrelated
- energy is highly compacted
- reasonable robust relative to
channel errors

Transform Coding
– A form of lossy block coding, but it does
not use codebook
– Frequency domain
– Frequency transformation finds the
essential data in the image and coding is
accurate
– 8*8 pixel blocks
– Discrete Cosine Transform (DCT)
Why Do We Need International Standards?
• International standardization is conducted to achieve
inter-operability .
• Only syntax and decoder are specified.
• Encoder is not standardized and its optimization is left to the
manufacturer.
• Standards provide state-of-the-art technology that is
developed by a group of experts in the field.
• Not only solve current problems, but also anticipate the future
application requirements.
Compression standards: JPEG

Joint Photographic Experts Group
(JPEG)
• One of the most important image data compression
standards
• Developed for highly detailed gray-scale and color
images / photographs
• Most commonly used as a lossy image compression
method, but lossless modes exist as well
• JPEG uses several cascaded compression modes
• Adjustable compression scheme  number of
retained frequency components can be changed to
achieve different compression ratios
• DCT > Remove rare frequency components >
DPCM/RLE > Huffman
JPEG
(Intraframe coding)
• First generation JPEG uses DCT+Run length Huffman
entropy coding.
• Second generation JPEG (JPEG2000) uses wavelet
transform + bit plane coding + Arithmetic entropy
coding.
Why DCT Not DFT?
• DCT is similar to DFT, but can provide a better
approximation with fewer coefficients
• The coefficients of DCT are real valued instead of complex
valued in DFT.
The 64 (8 X 8) DCT Basis Functions
• Each 8x8 block can
be looked at as a
weighted sum of
these basis functions.
• The process of 2D
DCT is also the
process of finding
those weights.
Zig-zag Scan DCT Blocks
• Why? -- To group low frequency coefficients in top of
vector.
• Maps 8 x 8 to a 1 x 64 vector.
Original
JPEG
27:1
JPEG2000
27:1
Motion compression standards

Moving Picture Experts Group (MPEG)
• Intended for the mass distribution of motion video
sequences
• Compression-asymmetric = compression techniques
require more processing time and computing power
than the decompression ones
• In addition to coding techniques used with JPEG, MPEG
utilizes interframe coding methods



MPEG-1 use CD-ROM and Internet
MPEG-2 use DVD and Digi-TV
MPEG-4 most advanced technology