This document summarizes image compression techniques. It discusses why images need to be compressed to reduce file sizes and speed up transmission. It describes how digital images are composed of pixels and color components. The document then covers lossless compression algorithms like Run Length Encoding (RLE) and LZW, which use statistical redundancy or dictionaries to compress images without loss of information. It also mentions lossy compression techniques like quantization that can achieve higher compression ratios but result in some loss of visual quality.

1. TOPIC’S PRESENTATION:
IMAGE COMPRESSION
Prepared by:
SBAIH Nizar
2012/2013

2. PLAN:
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 Why compression ?
 About digital images.
 Lossless data compression.
 Lossy data compression.
 Conclusion.

3. Why compression ?
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 Image with 10 Megapixel
 Three color component (R,G,B).
 One byte by component.
 Memory occupation : 30 Mbyte by image.
 Stocking on disk ? Transmission over the network ?
Reduce its size on disk.
Speed transmission over a network.

4. About images
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It is acquired, created, processed and stored in binary
form. It is composed of a set of points called pixels.
Example: Image 1024 × 768 coded on 3 bytes
Number of pixels : 1024 × 768 = 786432 pixels
Image size : 1024 × 768 × 3 = 2359296 octets = 2,25 Mo

5. Performance criteria
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 Compression ratio is an important factor to differ between images :
 The Mean Square Error is the cumulative squared error
between the compressed and the original image :

6. Algorithm compression
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There are two types of compression:
Lossless compression :
 Perfect reconstruction.
 Statistical redundancy.
 Small compression ratio.
Lossy compression :
 Reconstructed image ≠ original image.
 Quantization.
 Visually lossless.
 High compression ratio.

7. Lossless compression
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There are three types of lossless
compression:
•Methods based redundancy (RLE).
•Statistical methods (Huffman).
•Methods based on dictionaries (LZW).

8. Run-length encoding
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 Definition :
Run-length encoding is a data compression algorithm that is
supported by most bitmap file formats, such as TIFF, BMP,
and PCX.
 Principle:
RLE works by reducing the physical size of a repeating string
of characters.

9. Run-length encoding
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 Example:
After RLE After RLE
AAAABBBC 4A3B1C ENSAS 1E1N1S1A1S
Gain = 25% Loss = 50%
 Rules for using RLE:
Rule 1 : The character must be repeated at least three times.
Rule 2 : If the sequence is not encoded, we above 00 followed by the
number of characters .
Rule 3 : If the sequence is odd, we copy 00 at the end of the
sequences .

10. Run-length encoding
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 Different methods to encode images:
There are a number of variants of run-length encoding. Image data is normally
run-length encoded by uniform paving points, along lines, or even zigzag.

11. LZW (LEMPEL-ZIV-WEICH)
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 Definition :
It is a method of compression dictionary based on reasons
that are more often than others.
 Principle:
 Repeated sequences are stored in a dictionary and
replaced by their address in the dictionary.
 The index is replaced by the sequence which is stored on a
bit number smaller than the sequence.

12. LZW (LEMPEL-ZIV-WEICH)
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 Example :
Size of image : 256*153*24 bits = 114 ko
Compression
LZW
The size of the image : 51,9 ko
Le taux de
compression est de
2,21

13. 13
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ATTENTION