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
CWI. Probability, Networks and Algorithms [PNA]
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.