Orthogonal Bandlet Bases for Geometric Images Approximation
نویسندگان
چکیده
This paper introduces orthogonal bandlet bases to approximate images having some geometrical regularity. These bandlet bases are computed by applying parameterized Alpert transform operators over an orthogonal wavelet basis. These bandletization operators depend upon a multiscale geometric flow that is adapted to the image, at each wavelet scale. This bandlet construction has a hierarchical structure over wavelet coefficients taking advantage of existing regularity among these coefficients. It is proved that Cα images having singularities along Cα curves are approximated in a best orthogonal bandlet basis with an optimal asymptotic error decay. Fast algorithms and compression applications are described. c © 2000 Wiley Periodicals, Inc.
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