C. Frigaard. Fast fractal 2D/3D image compression. Manuscript, Institute for Electronic Systems, Aalborg University, 1995.
Compression has become an important factor in relation to storage and transmission of large amounts of image data. Compression based on fractal theory is a new and promising technique for image data compression. The objective of this report is to improve fractal image compression, making it capable of handling many diverse image object such as grey level or color still images or image sequences and to reduce the complexity of the encoder. A major limitation of the fractal technique is the complexity of the encoding algorithm. To reduce complexity of the fractal scheme the total cartesian product of domain blocks and transformations used by the encoding scheme is not found, but instead a feature space is introduced: every domain and range block is pre-classified according to a set of invariant features, and range domain blocks in a n-dimensional feature space. Test results shows that the encoding of image objects with the use of this feature space is capable of reducing the complexity tremendously. The compression ratio and signal-to-noise ratio of the 2D encoding is in the same range as other fractal schemes, but with the encoding time reduced substantially. The encoding of 3D image arrays seems to outperform any other fractal scheme both with respect to image fidelity, compression ratio and encoding time.
@Misc{Frig95,
Author = {Frigaard, C.},
Title = {Fast fractal 2D/3D image compression},
Howpublished = {Manuscript, Institute for Electronic Systems, Aalborg University},
Year = {1995}
}