D. Saupe, R. Hamzaoui, H. Hartenstein. Fractal image compression - An introductory overview. In Fractal Models for Image Synthesis, Compression and Analysis, ACM SIGGRAPH'96 Course Notes 27, D. Saupe, J. Hart (eds.), New Orleans, Louisiana, 1996.
Fractal image compression is a new technique for encoding images compactly. It builds on local self-similarities within images. Image blocks are seen as rescaled and intensity transformed approximate copies of blocks found elsewhere in the image. This yields a self-referential description of image data, which - when decoded - shows a typical fractal structure. This paper provides an elementary introduction to this compression technique. We have chosen the similarity to a particular variant of vector quantization as the most direct approach to fractal image compression. We discuss the hierarchical quadtree scheme and vital complexity reduction methods. Furthermore, we survey some of the advanced concepts such as fast decoding, hybrid methods, and adaptive partitionings. We conclude with a list of relevant WEB resources including complete public domain C implementations of the method and a comprehensive list of up-to-date references.
@InProceedings{SaHaHar96,
Author = {Saupe, D. and Hamzaoui, R. and Hartenstein, H.},
Title = {Fractal image compression - An introductory overview},
BookTitle = {Fractal Models for Image Synthesis, Compression and Analysis, ACM SIGGRAPH'96 Course Notes 27},
editor = {Saupe, D. and Hart, J.},
Address = {New Orleans, Louisiana},
Month = {},
Year = {1996}
}