This document provides an overview of LZW coding technique for image compression. It discusses that LZW coding is a lossless compression scheme used for formats like GIF, TIFF, and PDF. It works by assigning the first 256 values (0-255) in an 8-bit grayscale image to a dictionary, and then adding new sequences encountered in the image to the dictionary. As the image is scanned, the encoded output consists of dictionary entries. The document provides an example and illustrates the encoding process. It notes advantages like high compression ratios without needing probability knowledge, and disadvantages like potential unused dictionary entries. It concludes that LZW can be used to compress files like TIFF, GIF, PDF, and text files.

1. LZW coding
By
Md. Fazle Rabbi
16CSE057

2. 4.2
CONTENTS
• An overview of Image compression
• An Introduction to LZW coding technique
• Methodology (Algorithm) LZW coding
• Advantages and Disadvantages of LZW coding
• Applications of LZW coding

3. 4.3
An overview of Image compression
• Goals of compression
a) Remove redundancy
b) Reduce storage required and hence the cost
c) Reduced bandwidth can be used
• Compression modes
1) Lossless compression
Preserve all information, perfectly recoverable.
2) Lossy compression
Throw away perceptually insignificant information
and cannot recover all bits

4. 4.4
Introduction To LZW
• Lossless Compression
• Compression scheme for Gif, TIFF and PDF
• For 8-bit grayscale images, the first 256 words are
assigned to grayscales 0, 1, …255
• As the encoder scans the image, the grayscale
sequences not in the dictionary are placed in the next
available location.
• The encoded output consists of dictionary entries.

5. 4.5
Example
• Consider an image of size 512*512, 8 bit image.
Uncompressed TIFF Version of this image requires 286,740
bytes of disk space
• Using TIFF's LZW compression option, however,the resulting
file is 224,420 bytes.
• The compression ratio ,C= (286740 / 224420)= 1.277
• For Huffman encoded representation of the same image
achieves compression ratio, C=1.077.
• The additional compression realized by LZW approach is due
to removal of Image's spatial redundancy.

6. 4.6
Encoding a sequence of symbols using LZW Coding
• The encoding process is be illustrated for one line of image
having the following intensity values in sequence: 32 32 34 32
34 32 32 33 32 32 32 34.
Consider the table as below:

7. 4.7
Encoding a sequence of symbols using LZW Coding
Sequence: 32 32 34 32 34 32 32 33 32 32 32 34.

8. 4.8
Advantages and disadvantages of LZW coding
Advantages:
• Extremely effective when there are repeated patterns in the data that
are widely spread
• Prior knowledge of probability of occurrence of symbols to be encoded is
not required.
• Simple coding technique with high compression ratio.
• LZW compression is fast
• Lossless compression technique
Disadvantages:
• Creates entries in the dictionary that may never be used.
• LZW is a fairly old compression technique

9. 4.9
Applications of LZW coding
LZW compression can be used in a variety of file formats:
• TIFF (tagged image file format )files
• GIF (graphic interchange format ) files
• PDF(portable document format) files
• Unix Compress, gzip.
• Suitable for compressing text files

10. 4.10
Thank You