Image compression using the W-transform | Zendy

William D. Reynolds | Zendy

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Image compression using the W-transform

Author(s) -

William D. Reynolds

Publication year - 1995

Publication title -

osti oai (u.s. department of energy office of scientific and technical information)

Language(s) - English

Resource type - Reports

DOI - 10.2172/195703

Subject(s) - wavelet transform , s transform , constant q transform , harmonic wavelet transform , signal (programming language) , algorithm , discrete wavelet transform , hartley transform , fractional fourier transform , mathematics , second generation wavelet transform , computer science , artificial intelligence , fourier transform , wavelet , mathematical analysis , fourier analysis , programming language

The authors present the W-transform for a multiresolution signal decomposition. One of the differences between the wavelet transform and W-transform is that the W-transform leads to a nonorthogonal signal decomposition. Another difference between the two is the manner in which the W-transform handles the endpoints (boundaries) of the signal. This approach does not restrict the length of the signal to be a power of two. Furthermore, it does not call for the extension of the signal thus, the W-transform is a convenient tool for image compression. They present the basic theory behind the W-transform and include experimental simulations to demonstrate its capabilities

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