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Image Compression using Wavelet Transform and Multiresolution Decomposition

Summary: Image Compression using Wavelet Transform and
Multiresolution Decomposition
to appear in IEEE Trans. on Image Processing, Vol. 5, No. 1, January 1996
A. Averbuch y , D. Lazar y M. Israeli z
y School of Mathematical Sciences, Tel Aviv University, Tel Aviv 69978, Israel
z Faculty of Computer Science, Technion, Haifa 32000, Israel
A scheme for image compression of black and white images based on the wavelet
transform is presented. The multiresolution and multifrequency nature of the discrete
wavelet transform is proved to be a powerful tool for representing the images which are
decomposed along the vertical and horizontal directions using the pyramidal multires­
olution scheme. The wavelet transform decomposes the image into a set of subimages
(which are called shapes) with different resolutions corresponding to different frequency
bands. Hence, different allocations are tested assuming that details at high resolution
and diagonal directions are less visible to the human eye. The resulted coefficients
are vector quantized using the LGB algorithm. By using an Error Correction method,
which approximates the error of the quantization of the reconstructed coefficients, we
optimize the tradeoff between low distortion and high compression rate while keeping
a low computational cost.
In the following work, several types of compression techniques were tested.


Source: Averbuch, Amir - School of Computer Science, Tel Aviv University


Collections: Computer Technologies and Information Sciences