Image Compression by Approximated 2D Karhunen Loeve Transform

  • Władysław Skarbek
  • Adam Pietrowcew
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1689)


Image compression is performed by 8 x 8 block transform based on approximated 2D Karhunen Loeve Transform. The transform matrix W is produced by eight pass, modified Oja-RLS neural algorithm which uses the learning vectors creating the image domain subdivision into 8 x 1 blocks. In transform domain, the stages of quantisation and entropy coding follow exactly JPEG standard principles. It appears that for images of natural scenes, the new scheme outperforms significantly JPEG standard: at the same bitrates it gives up to two decibels increase of PSNR measure while at the same image quality it gives up to 50% lower bitrates. Despite the time complexity of the proposed scheme is higher than JPEG time complexity, it is practical method for handling still images, as C++ implementation on PC platform, can encode and decode for instance LENA image in less than two seconds.


Discrete Cosine Transform Image Compression Quantisation Scale Entropy Code Quantisation Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Władysław Skarbek
    • 1
  • Adam Pietrowcew
    • 2
  1. 1.Department of Electronics and Information TechnologyWarsaw University of TechnologyWarszawaPoland
  2. 2.Department of InformaticsTechnical University of BialystokBialystok

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