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Image compression

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Title: Image compression


1
Image compression
2
Image Compression
  • Why?
  • Reducing transportation times
  • Reducing file size
  • A two way event - compression and decompression

3
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4
Compression categories
  • Compression Image coding
  • Still-image compression
  • Compression of moving image

5
INTERFRAME and INTRAFRAME PROCESSING
Intraframe Processing
6
Group discussionDiscuss, which compression and
coding method you know!
7
Image compression meters
  • Compress ratio
  • Original image size
  • Compressed image size
  • The larger the compression ratio, the smaller the
    result image

8
Image compression
  • Compression method is not same as the image
    file-interchange format.
  • Example TIFF -file format supports several
    compression methods

9
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10
Why Can We Compress?
  • Spatial redundancy
  • Neighboring pixels are not independent but
    correlated
  • Temporal redundancy

11
Information vs Data
REDUNDANTDATA
INFORMATION
DATA INFORMATION REDUNDANT DATA
12
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

13
Image compression symmetry
14
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 --gt HSB, when Hue and Saturation components
    are well compressed

15
Color imagecompression
HUE
BRIGHTNESS
SATURATION
16
Lossless image compression
  • Image can be decompressed back to original
  • Used when images future purpose of use is not
    known, example space exploration imagery is often
    studied for years following its origination

17
Run-Length Coding
18
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

19
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

Arrange values in descending frequency of
occurrence
Assign Huffman variable-length codes
Brightness Histogram
Huffman Code Image Data
Raw Image Data
Substitute Huffman codes
Append code list
0,10,0,1100 1111,11011
98,100,103, 87,86,95...
The flow of the Huffman coding operation.
20
Huffman coding
character number Huffman code a
(97) 45 1 1 b (98) 23 1 0 01 c
(99) 2 0 0 000 d (100) 1 0 1 0010 CR
(13) 1 1 1 00111 LF (10) 1 0 00110
28
5
3
2
21
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,
    Blueray, WWW) and rate constrained environment
    where lossless methods can not provide enough
    compression ratio

22
Predictive Coding
  • Based on the assumption that pixels 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)

23
DPCM (Differential Pulse Code Modulation)
24
Block Coding
  • Searching for repeated patterns (mostly in rows)
  • Pixel patterns are put in Codebook
  • Original images pixel pattern is replaced by
    codebook index in compressed image

25
Block Coding
  • LZW- compression (Lempel-Ziv-Welch)
  • Compression ratio 21 - 31
  • Starting with a 256 single-pixel long codebook -gt
    adding until it reaches its maximum length
  • LZWHuffmann, where most common pixel patterns
    get shortest codes

26
TRANSFORM CODING
27
  • 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
  • 88 pixel blocks
  • Discrete Cosine Transform (DCT)

28
File formats and compression methods
  • Standards crucial, so pictures are transportable
    between different systems
  • Compression standards
  • CCITT group 3 and 4 (Fax-standard)
  • Joint Bi-level Image Expert Group (JBIG)
  • Joint Photographic Experts Group (JPEG)
  • Motion picture
  • CCITT Recommendation H.261 H.264
  • Moving Picture Experts Group (MPEG)

29
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.

30
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 à number of
    retained frequency components can be changed to
    achieve different compression ratios
  • DCT gt Remove rare frequency components gt
    DPCM/RLE gt Huffman

31
JPEG(Intraframe coding)
  • First generation JPEG uses DCTRun length Huffman
    entropy coding.
  • Second generation JPEG (JPEG2000) uses wavelet
    transform bit plane coding Arithmetic entropy
    coding.

32
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.

33
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.


34
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.


35
Original
36
JPEG 271
37
JPEG2000 271
38
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 (Blueray, www)
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