Computational complexity of fractal image compression algorithm

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Abstract

This study presents insights into the computational complexity of fractal image compression (FIC) algorithms. Unlike JPEG, a fractal encoder necessitates more CPU time in contrast to the decoder. The study examines various factors that impact the encoder and its computational cost. Many researchers have dedicated themselves to the field of fractal encoding to overcome the computational cost of the FIC algorithm. Here, this study offers a look over the approaches in the aspect of time complexity. The automated baseline fractal compression algorithm is studied to demonstrate the understanding of delay in the encoder. The study establishes how various approaches trade-off between the quality of decoder, compression ratio, and CPU time. The experiment section shows the bargain between fidelity criteria of the baseline algorithm.

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Gupta, R., Mehrotra, D., & Tyagi, R. K. (2020, December 24). Computational complexity of fractal image compression algorithm. IET Image Processing. John Wiley and Sons Inc. https://doi.org/10.1049/iet-ipr.2019.0489

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