Title :
On the reconstruction aspects of moment descriptors
Author :
Pawlak, Miroslaw
Author_Institution :
Dept. of Electr. & Comput. Eng., Manitoba Univ., Winnipeg, Man., Canada
fDate :
11/1/1992 12:00:00 AM
Abstract :
The problem of reconstruction of an image from discrete and noisy data by the method of moments is examined. The set of orthogonal moments based on Legendre polynomials is employed. A general class of signal-dependent noise models is taken into account. An asymptotic expansion for the global reconstruction error is established. This reveals mutual relationships between a number of moments, the image smoothness, sampling rate, and noise model characteristics. The problem of an automatic (data-driven) section of an optimal number of moments is studied. This is accomplished with the help of cross-validation techniques
Keywords :
image reconstruction; polynomials; Legendre polynomials; asymptotic expansion; cross-validation techniques; discrete data; global reconstruction error; image reconstruction; image smoothness; method of moments; moment descriptors; noisy data; orthogonal moments; sampling rate; signal-dependent noise models; Computer errors; Convergence; Image reconstruction; Image sampling; Layout; Marine vehicles; Moment methods; Pattern matching; Pattern recognition; Polynomials;
Journal_Title :
Information Theory, IEEE Transactions on
