Fractal Image Compression Using Canonical Huffman Coding

Authors

  • Shree Ram Khaitu Department of Computer Engineering, Khwopa Engineering College, Purbanchal University
  • Sanjeeb Prasad Panday Department of Electronics and Computer Engineering, Pulchowk Campus, Institute of Engineering, Tribhuvan University, Kathmandu

DOI:

https://doi.org/10.3126/jie.v15i1.27718

Keywords:

PSNR, Image Compression, Entropy encoding, Huffman Coding, Canonical Huffman Coding

Abstract

 Image Compression techniques have become a very important subject with the rapid growth of multimedia application. The main motivations behind the image compression are for the efficient and lossless transmission as well as for storage of digital data. Image Compression techniques are of two types; Lossless and Lossy compression techniques. Lossy compression techniques are applied for the natural images as minor loss of the data are acceptable. Entropy encoding is the lossless compression scheme that is independent with particular features of the media as it has its own unique codes and symbols. Huffman coding is an entropy coding approach for efficient transmission of data. This paper highlights the fractal image compression method based on the fractal features and searching and finding the best replacement blocks for the original image. Canonical Huffman coding which provides good fractal compression than arithmetic coding is used in this paper. The result obtained depicts that Canonical Huffman coding based fractal compression technique increases the speed of the compression and has better PNSR as well as better compression ratio than standard Huffman coding.

 

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Published

2020-02-16

How to Cite

Khaitu, S. R., & Panday, S. P. (2020). Fractal Image Compression Using Canonical Huffman Coding. Journal of the Institute of Engineering, 15(1), 91–105. https://doi.org/10.3126/jie.v15i1.27718

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Articles