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Novel Method of Image Compression using Angular Domain Concept to Achieve High Compression Rate

by Pravin B.pokle, Narendra G. Bawane
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 108 - Number 6
Year of Publication: 2014
Authors: Pravin B.pokle, Narendra G. Bawane
10.5120/18915-0234

Pravin B.pokle, Narendra G. Bawane . Novel Method of Image Compression using Angular Domain Concept to Achieve High Compression Rate. International Journal of Computer Applications. 108, 6 ( December 2014), 23-27. DOI=10.5120/18915-0234

@article{ 10.5120/18915-0234,
author = { Pravin B.pokle, Narendra G. Bawane },
title = { Novel Method of Image Compression using Angular Domain Concept to Achieve High Compression Rate },
journal = { International Journal of Computer Applications },
issue_date = { December 2014 },
volume = { 108 },
number = { 6 },
month = { December },
year = { 2014 },
issn = { 0975-8887 },
pages = { 23-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume108/number6/18915-0234/ },
doi = { 10.5120/18915-0234 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:42:16.267760+05:30
%A Pravin B.pokle
%A Narendra G. Bawane
%T Novel Method of Image Compression using Angular Domain Concept to Achieve High Compression Rate
%J International Journal of Computer Applications
%@ 0975-8887
%V 108
%N 6
%P 23-27
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image compression plays vital role in the field of the corporate world, entertainment industry, multimedia, education communications and even at home. The main objective of Image compression is to minimize the size of image in bytes by reducing the redundancy of the image data without degrading the quality of image that results in the reduction of file size so that more images can be stored in a given amount of disk or memory space and also reduces the time required to send the images over the network. Inspired by the recent advancements in the image compression techniques, we proposed an image compression framework based on the pixel-wise fidelity. The proposed method is used to reduce the bit rate of the pixels of the image for the compression by using angular transformation. In the proposed algorithm we used the normalization technique and the inverse sine transformation to get the optimized and compressed image as an output. Finally the results are compared with different methods for MSE, PSNR and the visual appearance after decoding of image.

References
  1. Shantanu D. Rane and Guillermo Sapiro, Member, IEEE,"Evaluation of JPEG-LS, the New Lossless and Controlled-Lossy Still Image Compression Standard, for Compression of High-Resolution Elevation Data", IEEE Transactions on Geoscience and Remote sensing, VOL. 39, NO. 10, Oct. 2001
  2. Kadono, S, Tahara O and Okamoto N (2001) "Encoding ofcolor still pictures wavelet transform and vector quantization", Canadian Conference on Electrical and Computer Engineering 2:931–936
  3. I. Hontsch and L. J. Karam, "Adaptive image coding with perceptual distortion control," IEEE Trans. Image Processing, vol. 11, pp. 213-222,March 2002.
  4. R. Cilibrasi, P. M. B. Vitanyi; "Clustering by Compression", IEEE Transaction on Information Theory, vol. 51, N° 4, April 2005, pp 1523 - 1545.
  5. S. Rooij, P. Vitanyi, "Approximating Rate-Distortion Graphs of individual Data: Experiments in Lossy Compression and Denoising", IEEE Transaction on Computers, vol. 61, N° 3, March 2012, pp. 395-407.
  6. J. Shi and J. Malik, ?Normalized cuts and image segmentation, IEEE Trans. PatternAnal. Mach. Intell. , vol. 22, no. 8, pp. 888–905, Aug. 2000.
  7. C. en Guo, S. -C. Zhu, and Y. N. Wu, "Towards a mathematica theory of primal sketch and sketchability," in Proc. IEEE Int. Conf. Computer vision (ICCV'03), 2003, pp. 1228–1235.
  8. C. C. Chang and J. C. Chuan, "An image intellectual Property Protection scheme for graylevel images using visual secret sharing strategy," Pattern Reconition Letters, vol. 23, pp. 931-941, June 2002.
  10. M. Mohammed Sathik, "Feature Extracton on Color ED x-Ray Images by Bit-plane Slicing Technique", International Journal of Engg. Science and Technology, Vol. 2(7), 2010, 2820-2824.
  11. Z. Zhang , W. Li & B. Li, "An Improving Technique of Color Histogramam in Segmentation Retrieval. "2009 Fifth International Conference on Information Assurance and Security, 381 -384(2009).
  12. Mr. N S T Sai and R. C. Patil, Image Retrieval Using Bit-Plane Pixel Distribution, International Journal of Computer Science and Information Technology, Vol. 3, June 2011.
  13. Aksay et al. , "End –to -end stereoscopic video streaming with contentadaptive rate and format control," Signal Processing: Image Communication, vol. 22, pp. 157 - 168, 2007.
  14. A. B. R. H. S. a. P. E. S. Z. Wang, "Image quality assessment: from error visibility to structural similarity," IEEE Trans. Image Processing, vol. 13, no. 4, pp. 600- 612, 2004.
Index Terms

Computer Science
Information Sciences

Keywords

Image compression Normalization Angular transform Bit plane slicing MSE PSNR.

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