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5. Orthonormal Bases of Wavelets and Multiresolution Analysis

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Abstract

The first constructions of smooth orthonormal wavelet bases seemed a bit miraculous, as illustrated by the proof in §4.2.A that the Meyer wavelets constitute an orthonormal basis. This situation changed with the advent of multiresolution analysis, formulated in the fall of 1986 by Mallat and Meyer. Multiresolution analysis provides a natural framework for the understanding of wavelet bases, and for the construction of new examples. The history of the formulation of multiresolution analysis is a beautiful example of applications stimulating theoretical development. When he first learned about the Meyer basis, Mallat was working on image analysis, where the idea of studying images simultaneously at different scales and comparing the results had been popular for many years (see, e.g., Witkin (1983) or Burt and Adelson (1983)). This stimulated him to view orthonormal wavelet bases as a tool to describe mathematically the “increment in information” needed to go from a coarse approximation to a higher resolution approximation. This insight crystallized into multiresolution analysis (Mallat (1989), Meyer (1986)).

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The first constructions of smooth orthonormal wavelet bases seemed a bit miraculous, as illustrated by the proof in §4.2.A that the Meyer wavelets constitute an orthonormal basis. This situation changed with the advent of multiresolution analysis, formulated in the fall of 1986 by Mallat and Meyer. Multiresolution analysis provides a natural framework for the understanding of wavelet bases, and for the construction of new examples. The history of the formulation of multiresolution analysis is a beautiful example of applications stimulating theoretical development. When he first learned about the Meyer basis, Mallat was working on image analysis, where the idea of studying images simultaneously at different scales and comparing the results had been popular for many years (see, e.g., Witkin (1983) or Burt and Adelson (1983)). This stimulated him to view orthonormal wavelet bases as a tool to describe mathematically the “increment in information” needed to go from a coarse approximation to a higher resolution approximation. This insight crystallized into multiresolution analysis (Mallat (1989), Meyer (1986)).

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Available abstract

The first constructions of smooth orthonormal wavelet bases seemed a bit miraculous, as illustrated by the proof in §4.2.A that the Meyer wavelets constitute an orthonormal basis. This situation changed with the advent of multiresolution analysis, formulated in the fall of 1986 by Mallat and Meyer. Multiresolution analysis provides a natural framework for the understanding of wavelet bases, and for the construction of new examples. The history of the formulation of multiresolution analysis is a beautiful example of applications stimulating theoretical development. When he first learned about the Meyer basis, Mallat was working on image analysis, where the idea of studying images simultaneously at different scales and comparing the results had been popular for many years (see, e.g., Witkin (1983) or Burt and Adelson (1983)). This stimulated him to view orthonormal wavelet bases as a tool to describe mathematically the “increment in information” needed to go from a coarse approximation to a higher resolution approximation. This insight crystallized into multiresolution analysis (Mallat (1989), Meyer (1986)).

Key concepts: Orthonormal basis, Multiresolution analysis, Wavelet, Basis (linear algebra), Legendre wavelet, Wavelet transform, Mathematics, Algorithm

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