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Using Tensor Products to Apply Wavelets to Images

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Linear Algebra, Signal Processing, and Wavelets - A Unified Approach
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Abstract

Previously we have used wavelets to analyze sound. We would also like to use them in a similar way to analyze images. In Chap. 8 we used the tensor product to construct two dimensional objects (i.e. matrices) from one-dimensional objects (i.e. vectors). Since the spaces in wavelet contexts are function spaces, we need to extend the strategy from Chap. 8 to such spaces. In this chapter we will start with this extension, then specialize to the resolution spaces V m, and extend the DWT to images. Finally we will look at several examples.

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Notes

  1. 1.

    Note also that MATLAB has a wavelet toolbox which could be used for these purposes. We will however not go into the usage of this, since we implement the DWT from scratch.

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Ryan, Ø. (2019). Using Tensor Products to Apply Wavelets to Images. In: Linear Algebra, Signal Processing, and Wavelets - A Unified Approach. Springer Undergraduate Texts in Mathematics and Technology. Springer, Cham. https://doi.org/10.1007/978-3-030-01812-2_9

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