Open AccessFractal image coding algorithm using particle swarm optimisation and hybrid quadtree partition scheme
Author(s) -
XingYuan Wang,
DouDou Zhang,
Na Wei
Publication year - 2015
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2014.0001
Subject(s) - quadtree , particle swarm optimization , algorithm , fractal , range (aeronautics) , partition (number theory) , pixel , coding (social sciences) , computer science , mathematics , encoder , compression ratio , artificial intelligence , pattern recognition (psychology) , mathematical analysis , statistics , combinatorics , materials science , automotive engineering , engineering , composite material , internal combustion engine , operating system
In this study, a novel fractal image coding algorithm using particle swarm optimisation (PSO) and hybrid quadtree partition (QP) scheme is proposed. A method called PSO strategy based on range block classification (PSO‐RC) is presented instead of utilising the PSO method in the whole range pool. This new idea can enhance the compression ratio significantly and speed up the encoder. Moreover, a PSO‐RC hybrid QP (PSO‐RCQP) scheme is adopted in order to improve the quality of the retrieved image further. Firstly, the range blocks are divided into two categories based on the standard deviation feature. Secondly, the range blocks are encoded using either the PSO approach or storing the average pixel values directly. Thirdly, the range blocks with large matching errors when using PSO scheme employ the proposed QP method. The simulation results show that the proposed algorithm can obtain good quality and higher compression ratio other than shorten the encoding time.