Fractals everywhere
Fractal image compression: theory and application
Fractal image compression: theory and application
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
The data compression book (2nd ed.)
The data compression book (2nd ed.)
Construction of fractal objects with iterated function systems
SIGGRAPH '85 Proceedings of the 12th annual conference on Computer graphics and interactive techniques
Harnessing chaos for image synthesis
SIGGRAPH '88 Proceedings of the 15th annual conference on Computer graphics and interactive techniques
Region-based fractal image compression using heuristic search
IEEE Transactions on Image Processing
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In this paper, we propose a method of regional search for fractal image compression and decompression in a PVM system. In this method, the search for the partitioned iterated function system (PIFS) is carried out in a region of the image instead of over the whole image. Because the area surrounding of a partitioned block in an image is similar to this block possibly, finding the fractal codes by regional search results in increased compression ratios and decreased compression times. When implemented on the PVM, the regional search method of fractal image compression has the minimum communication cost. We can compress a 1024 × 1024 Lenna's image on a PVM with 4 Pentium II-300 PCs in 13.6 seconds, with a compression ratio 6.34; by comparison, the conventional fractal image compression requires 176 seconds and has a compression ratio 6.30. In the future, we can apply this method to fractal image compression using neural networks.