STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Image Processing & Pattern Recognition Progress

Fractal Geometry and Its Application to Image Compression

  1. Tejas Gandhi
  2. Hetal Patel
  3. Darshana Prajapati

Abstract

This paper presents the concept of fractal and its geometry with the explanation of how natural objects require different geometry rather than traditional Euclidean geometry and also discusses mathematics of fractals with the simulation results of generated fractal and applications of the fractal geometry in image compression. Image compression using fractal has a major drawback of large encoding time and several algorithms have been developed to reduce the encoding time for compression. In this paper, the algorithm of image compression using fractal and DCT for color images is presented with experimental results. In order to minimize the search time for domain blocks no-search technique was used in this algorithm. To avoid low quality of the decompressed image quad tree scheme was used with the algorithm and by predefining appropriate threshold value at each level of quad tree and by choosing suitable contrast scaling factor the accuracy of the output for the algorithm was increased.Cite this ArticleTejas Gandhi, Hetal Patel, Darshana Prajapati. Fractal Geometry and its Application to Image Compression. Journal of Image Processing & Pattern Recognition Progress. 2015; 2(2): 4–12p.

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