Similarity based optimization to fractal image encoding based on multithreading parallelization


E Higher compression time is a major issue in adoption of fractal image coding even though it offers various advantages in terms of higher compression ratio, higher resolution, and lower decompression time. Many optimizations have been proposed earlier to reduce the computation time in terms of parallelism and encoding space reduction. This work proposes an integrated approach combining both multithreaded parallelism and similarity based encoding space reduction to diminish the time of compression in Fractal image coding. The compression time of the proposed integrated method is tested for images of different resolution and the proposed solution is able to reduce the compression time by almost 4.4 times compared to existing fractal image compression techniques.


Fractal image compression; Fractal image coding; Data parallelism; Multithreading; SSIM; Entropy

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