Monagi Alkinani, Fall 2011, "Context-Based Multiple
Dictionaries LZ Image Compression", Computer Science
Department, University of Western Ontario, Canada.
M.Sc. Thesis Abstract
Dictionary-based encoding depends on similarity between
characters. When encoding strings, encoder replaces string by
a much shorter bytes that is a reference to a previous
similar encoded string. Lempel and Ziv (LZ) 1977&1978
algorithms are considered the foundation of the
Many algorithms have been presented to improve the
performance of the LZ algorithms. LZR, LZSS, LZB, LZH,
Improved-LZSS, LZFG, LZRW, SA-LZ77, Fixed-LZ77, LZAC,
LZFFG-PM, DifLZ, LZP, LZGT, LZW and CSD are modifications to
improve the speed and/or the compression ratio of LZ. Perhaps
the best LZ improvement includes, LZP which combining LZ
algorithms with prediction by partial matching encoding (PPM).
LZ algorithms are originally used for text compressions.
Pixels in images are highly correlated with their
neighbouring pixels. Properly extending LZP to encode images,
where the 2D nature of image is exploited, would produce
better compression results. We have run several experiments
to study one of LZ78 improvements, which is sub-dictionaries
ethod (CSD). CSD uses multiple dictionaries instead of just
one (though it is a 1st order PPM), more compression ratios
In our presentation, In this presentation, we will talk about
the various LZ modifications. We will discuss the efficiency
of these modifications based on the result of each
modification when running Calgary Corpus standard test. We
will also talk about the experiments which we run to show the
improvement in LZ78, and how the usage of 2D in images can
improve the compression ratio.