LZW compression and research papers

1. LZW COMPRESSION
Presented By:
Rabia Nazir
12-Mtech-2015
DEPARTMENT OF COMPUTER SCIENCE & IT

2. CONTENTS
 Introduction
 Implementation of lzw compression
 Improving lzw compression
 Advantages
 Limitations
 Applications
 Implementation in matlab
 References

3. ABOUT LZW COMPRESSION
 Abraham Lempel, Jakob Ziv and Terry Welch
 Adaptive dictionary based technique
 If dictionary overflows, add a bit to each code
 Uses greedy approach to divide text
 Encoding: dictionary initialized to contain single
character strings
 Scanning successively larger substrings untill no
match found

4. AMERICAN JOURNAL OF ENGINEERING RESEARCH
LZW DATA COMPRESSION [1]

5. DECODING

6. ADVANTAGES
 Most popular Lossless compression
 Reduces file size containing repetitive data
 No need to pass string table to decompression
 Table can be recreated
 Fast and simple

7. INTERNATIONAL JOURNAL OF INFORMATION SCIENCES AND TECHNIQUES
DESIGN AND IMPLEMENTATION OF LZW IMAGE
COMPRESSION[2]
o Evaluated by finite state machine in VHDL
o Dictionary based on content access memory
o Each character replaced by less number of bits
than its ASCII value
 Simulations by Xilinix ISE simulator synthesises
HDL
 Reduction of storage by 60.25% & increased
compression rate by 30.3%

8. ARCHITECTURE
Finite state machine architecture
Generate code

9. LIMITATIONS OF LZW COMPRESSION
 Suitable for repetitive data only
 Type of image & number of colors must be
considered
 Can’t be used in images with shadows or gradient

10. EUROPEAN JOURNAL OF SCIENTIFIC RESEARCH
IMPROVING LZW IMAGE COMPRESSION [3]
o Focuses on LZW, Adaptive Huffman Coding and Bit Plane
Slicing
o Adaptive Huffman builds frequency table according to data
statistics
o Bit plane slicing highlights contribution of each bit in
appearance of image
o Slice gray scale images into 8 binary images using bit plane
slicing
o Initialize dictionary with 0 & 1
o Each output associates frequency counter to phase in with
binary codes; to decrease number of bits
o Results show improvement depends on type of image;
correlation between intensities

11. o Compression ratio of gray scale images is approx. 102%
over standard LZW algorithm

12. Compression ratio of colored images is approx. 55.6% over
standard LZW algorithm

13. IMPLEMENTATION OF LZW IN MATLAB

14. APPLICATIONS
 Medical science
 ECG [4]
 Used in GIF, TIFF and PDF files
 Used in programs like PKZIP
 Hardware devices

15. REFERENCES
[1] Dheemanth H N ,“LZW Data Compression”, American
Journal of Engineering Research (AJER) e-ISSN : 2320-0847 p-
ISSN : 2320-0936 Volume-03, Issue-02, pp-22-26
[2] Simrandeep kaur, Student and V.Sulochana Verma ,Project
Consultant, “Design and Implementation of LZW Data
Compression”, International Journal of Information Sciences and
Techniques (IJIST) Vol.2, No.4, July 2012
[3] Sawsan A. Abu Taleb, Hossam M.J. Musafa, Asma’a M.
Khtoom, Islah K. Gharaybih, “Improving LZW Image
Compression”, European Journal of Scientific Research ISSN
1450-216X Vol.44 No.3 (2010), pp.502-509
[4] Mridul Kumar Mathur, Dr. Akhil Ranjan Garg , Prof. Mukesh
Upadhayay, “Application of LZW Technique for ECG Data
Compression”, International Journal of Advances in Computer
Networks and its Security.