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Advances in Computer Science and Information Technology. Computer Science and Information Technology. Second International Conference, CCSIT 2012, Bangalore, India, January 2-4, 2012. Proceedings, Part III

Research Article

Compression of Gray Scale Images Using Linear Prediction on Wavelet Coefficients

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  • @INPROCEEDINGS{10.1007/978-3-642-27317-9_6,
        author={P. Arya Devi and M. Mini},
        title={Compression of Gray Scale Images Using Linear Prediction on Wavelet Coefficients},
        proceedings={Advances in Computer Science and Information Technology. Computer Science and Information Technology. Second International Conference, CCSIT 2012, Bangalore, India, January 2-4, 2012. Proceedings, Part III},
        proceedings_a={CCSIT PART  III},
        year={2012},
        month={11},
        keywords={Image Compression bits per pixel (bpp) wavelet transform linear predictive coding (LPC) correlation},
        doi={10.1007/978-3-642-27317-9_6}
    }
    
  • P. Arya Devi
    M. Mini
    Year: 2012
    Compression of Gray Scale Images Using Linear Prediction on Wavelet Coefficients
    CCSIT PART III
    Springer
    DOI: 10.1007/978-3-642-27317-9_6
P. Arya Devi1,*, M. Mini1,*
  • 1: Model Engineering College
*Contact email: aryabinoy@gmail.com, mininair@mec.ac.in

Abstract

Each year, terabytes of image data- both medical and non medical- are generated which substantiates the need of image compression. In this paper, the correlation properties of wavelets are utilised in linear predictive coding to compress images. The image is decomposed using a one dimensional wavelet transform. The highest level approximation and a few coefficients of details in every level are retained. Using linear prediction on these coefficients the image is reconstructed.With less predictors and samples from the original wavelet coefficients compression can be achieved. The results are appraised in objective and subjective manner.

Keywords
Image Compression bits per pixel (bpp) wavelet transform linear predictive coding (LPC) correlation
Published
2012-11-09
http://dx.doi.org/10.1007/978-3-642-27317-9_6
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