Computational complexity of fractal image compression algorithm. Issue 17 (26th February 2021)

• Record Type: Journal Article
• Authors: Gupta, Richa; Mehrotra, Deepti; Tyagi, Rajesh Kumar
• Is Part Of: IET image processing. Volume 14:Issue 17(2020)
• Page Start: 4425
• Page End: 4434
• Publication Date: 2021-02-26
• Subjects: data compression -- computational complexity -- fractals -- image coding; computational complexity -- fractal image compression algorithm -- fractal encoder -- CPU time -- decoder -- computational cost -- fractal encoding -- FIC algorithm -- time complexity -- automated baseline fractal compression algorithm -- compression ratio -- baseline algorithm; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2019.0489
• Languages: English
• ISSNs: 1751-9659

Abstract

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.