A Study on Partitioned Iterative Function Systems for Image Compression

  • Authors:
  • Suman K. Mitra;C.A. Murthy;Malay K. Kundu

  • Affiliations:
  • Machine Intelligence Unit, Indian Statistical Institute, 203, B. T. Road, Calcutta 700035. INDIA. Email: res9432@isical.ac.in murthy@isical.ac.in malay@isical.ac.in;Machine Intelligence Unit, Indian Statistical Institute, 203, B. T. Road, Calcutta 700035. INDIA. Email: res9432@isical.ac.in murthy@isical.ac.in malay@isical.ac.in;(Correspd.) Machine Intelligence Unit, Indian Statistical Institute, 203, B. T. Road, Calcutta 700035. INDIA. Email: res9432@isical.ac.in murthy@isical.ac.in malay@isical.ac.in

  • Venue:
  • Fundamenta Informaticae
  • Year:
  • 1998

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Abstract

The technique of image compression using Iterative Function System (IFS) is known as fractal image compression. An extension of IFS theory is called as Partitioned or local Iterative Function System (PIFS) for coding the gray level images. The theory of PIFS appears to be different from that of IFS in the sense of application domain. Assuming the theory of PIFS is the same as that of IFS, several techniques of image compression have been developed. In the present article we have studied the PIFS scheme as a separate one and proposed a mathematical formulation for the existence of its attractor. Moreover the results of a Genetic Algorithm (GA) based PIFS technique [1] is presented. This technique appears to be efficient in the sense of computational cost.