On an efficient sparse representation of objects of general shape via continuous extension and wavelet approximation (with Z. Zhang), International Journal of Wavelets, Multiresolution, and Information Processing, vol. 8, no. 2, pp. 253-269, 2010.
Abstract
In this paper, we discuss the continuous extension and wavelet approximation of
the detected object on a general domain of R2.
We first extend continuously the image to a square T and such that it
vanishes on boundary ∂T. On T \ Ω, the extension has a
simple and clear representation which is determined by the equation of the
boundary ∂T. We expand the extension into wavelet series on
R2. Since the extension tool is polynomials,
by the moment theorem, we know that the sequence of wavelet coefficients
obtained by us is sparse. Therefore, we can approximate and analyze the
internal information of the object very well even if we only store a few
wavelet coefficients.
Keywords: object-oriented image analysis, continuous extension, wavelet approximation
Get the full paper (Revised on 07/11/09): PDF file.
Get the official version via doi:10.1142/S0219691310003493.
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