Open AccessAn Improved Irreversible Fractal Scheme for Medical Image Compression
Author(s) -
N. A. Z. Rahman,
Rizalafande Che Ismail,
A. H. M. Shapri
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/932/1/012069
Subject(s) - fractal compression , quadtree , image compression , computer science , compression ratio , peak signal to noise ratio , image (mathematics) , fractal , fractal transform , computation , artificial intelligence , algorithm , data compression , computer vision , mathematics , image processing , mathematical analysis , internal combustion engine , automotive engineering , engineering
In this paper, an improved fractal image compression (FIC) based on peer adjacent scheme and domain classification was proposed. The proposed method has low computation cost since it contains no search operations, thus becoming fast irreversible fractal scheme. Comprehensive experiments on a standard test image and several types of digital radiology images revealed that the proposed method is competitive when compared to established quadtree-based FIC techniques. The novelty of the proposed method lies in the use of this improved domain classification and mapping strategy for accurate and more precise FIC encoding. The empirical result of standard test image suggests that the proposed method is more competitive compared to the established schemes and achieves better performance in terms the peak signal-to-noise ratio (PSNR) and compression time averaging at 27.27 dB and 6.88 s, respectively. Also, the proposed method obtains an efficient compression ratio with 16.13 compared to others. Additionally, experiments involving various medical image modalities confirmed the superiority of the proposed method for practical applications of medical image compression.