Techniques in fractal geometry10/2/2023 With fractal compression, encoding is extremely computationally expensive because of the search used to find the self-similarities. įractal image compression has many similarities to vector quantization image compression. Other researchers attempt to find algorithms to automatically encode an arbitrary image as RIFS (recurrent iterated function systems) or global IFS, rather than PIFS and algorithms for fractal video compression including motion compensation and three dimensional iterated function systems. The initial square partitioning and brute-force search algorithm presented by Jacquin provides a starting point for further research and extensions in many possible directions - different ways of partitioning the image into range blocks of various sizes and shapes fast techniques for quickly finding a close-enough matching domain block for each range block rather than brute-force searching, such as fast motion estimation algorithms different ways of encoding the mapping from the domain block to the range block etc. This bottleneck of searching for similar blocks is why PIFS fractal encoding is much slower than for example DCT and wavelet based image representation. On the other hand, a large search considering many blocks is computationally costly. In the second step, it is important to find a similar block so that the IFS accurately represents the input image, so a sufficient number of candidate blocks for D i need to be considered.
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