Quadratic vs cubic spline-wavelets for image representations and compression
The Wavelet Transform generates a sparse multi-scale signal representation which may be readily compressed. To implement such a scheme in hardware, one must have a computationally cheap method of computing the necessary transform data. The use of semi-orthogonal quadratic spline wavelets allows one to maintain a suitable level of smoothness in the MRA whilst enabling cheap computation. Among the other advantages afforded by such a scheme are easily implementable boundary conditions and the existence of either linear or generalized linear phase in the wavelet filters, which has important consequences for signal compression.For image representation, a compressed spline MRA i.e., an MRA in which `redundant' basis coefficients have been ignored, allows us to generate a spline representation of an image which (for low order splines) may be readily displayed on specialised graphics hardware. Such a representation may also be used directly to generate a progressively transmitted image.
|CODING AND INFORMATION THEORY (acm E.4), Compression (acm I.4.2), Reconstruction (acm I.4.5), Camera calibration (acm I.4.1.0)|
|General harmonic expansions, frames (msc 42C15), Image processing (msc 68U10)|
|CWI. Probability, Networks and Algorithms [PNA]|
|Organisation||Signals and Images|
Marais, P.C, Blake, E.H, & Kuijk, A.A.M. (1997). Quadratic vs cubic spline-wavelets for image representations and compression. CWI. Probability, Networks and Algorithms [PNA]. CWI.