Image Compression Papers

Multiresolutional/Fractal Compression of Still and Moving Pictures  [.tar.gz, 1.8M]
Ph.D. Thesis, University of North Texas, Denton, TX, December 1993. The file is a .tar.gz archive of PostScript files representing thesis chapters and related documents.
 
Pyramidal Image Decompositions: A New Look
the full text of a paper presented as a poster at Data Compression Conference, Snowbird, Utah, 1993.
The thesis contains a more detailed discussion of this topic.
 
Self-similarity of the Multiresolutional Image/Video Decomposition: Smart Expansion as Compression of Still and Moving Pictures
the full text of the paper presented at Data Compression Conference, Snowbird, Utah, 1994.
The thesis contains a more detailed discussion of this topic.
 
Multiresolutional Piecewise-linear Image Decompositions: Quantization Error Propagation and Design of "Stable" Compression Schemes [.ps.gz, 136K]
the full text of the paper presented as a poster at Data Compression Conference, Snowbird, Utah, 1995.
 
Very subjective notes on Data Compression Conference 95 [.ps.gz, 17K]
This highly subjective paper contains notes on some presentations and rumors I picked up at the conference. A sizable part of the notes is devoted to a fascinating image compression technique by Dr. Karel Culik. His method achieves a 100:1 compression of grayscale pictures without any noticeable distortion. I took a stab at explaining how it works in simple signal-processing-lese terms, without resorting to finite automata. The Culik's method turns out to be related to both fractal compression and zero-tree encoding; in fact, a call it zerotree encoding of A*small_image+B-like transforms
 
Dissemination of compressed satellite imagery within the Navy SPAWAR Central Site Product Display environment
This presentation is a case study of integration of compression techniques within a satellite image communication component of an actual tactical weather information dissemination system. The paper describes history and requirements of the project, and discusses the information flow, request/reply protocols, error handling, and, especially, system integration issues. A case for a non-uniform compression of satellite imagery is presented, and its implementation in the current system is demonstrated. The paper gives special attention to challenges of moving the system towards the use of standard, non-proprietary protocols (smtp and http).
The paper itself is published in the proceedings of the NASA Science Information Management and Data Compression Workshop.
 
Compression with Iterated Function Systems, Finite Automata and Zerotrees: Grand Unification [.ps.gz, 40K]
the full text of a paper submitted to DCC'96: Data Compression Conference, Snowbird, Utah, 1996. From the abstract:
The paper offers a plain-term interpretation of Culik's image compression, a very capable yet undeservingly under-represented method giving spectacular results. The Culik's method will be explained in regular image processing terms, without resorting to finite state machines and similar lofty language. The interpretation is shown to be algorithmically related to an IFS fractal image compression method: an IFS can be exactly transformed into Culik's image code. Using this transformation, we will prove that in a self-similar (part of an) image any zero wavelet coefficient is the root of a zerotree, or its branch.

 
Very subjective notes on Data Compression Conference 96 [.ps.gz, 38K]
Again, this is a highly subjective paper describing a few most memorable DCC'96 presentations, along with my notes, references, and impressions of them. I talk about compression of images using Weighted Finite Automata (WFA), state of the art in the lossless coding of text, a (near)lossless compression of images, and wavelet coding.

A better half of the notes is devoted to a remarkable and stunning method of compressing images using Finite Automata, which was invented/discovered by Dr. Karel Culik. The notes are the result of pondering over Culik's presentation and paper. Along the way, I noticed and corrected a few typos in his paper. I really took a stab at "reverse-engineering" of the compression and decompression algorithms, showing how they work step-by-step, up to the point of pseudo-code and tracing through it.

Dr. Culik's website shows examples of WFA (Weighted Finite Automata) compression and contains his bibliography.

 


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