How to reconstruct a signal using the Discrete Haar Wavelet transform?

In summary: I'm looking for something more like "for an audio signal, do this..."In summary, the conversation is about a student's struggle with understanding and implementing the Discrete Haar Wavelet Transform for a school project. They are looking for helpful resources and a step-by-step algorithm for deconstructing and reconstructing an audio signal using the DHWT. The conversation also mentions the use of vector spaces and orthogonal functions in the DHWT process.
  • #1
XcKyle93
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Homework Statement



Hi, for a project for school, I need to implement the Discrete Haar Wavelet Transform to compress an audio signal. This would be fine and dandy, but I do not really understand how to use the the DHWT. Could anyone direct me towards some resources that would be very helpful in my understanding? If someone could provide a step-by-step algorithm that goes through the deconstruction and reconstruction of the signal, that would be nice. The textbook that I'm using is a math textbook, so it is more interested in proving properties of the filters & wavelets instead giving examples and exercises. This is great, until I actually need to apply it towards something.

Homework Equations


I know that there are vector spaces V and W that are orthogonal to each other; V is associated with the scaling function ∅, W is associated with the mother wavelet ψ. I think the first step in the DHWT is to pick a resolution j, but beyond that I don't understand.

The Attempt at a Solution

 
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  • #3
Sorry, I had seen that resource and it's much different from what we've done in class.
 

1. What is the Discrete Haar Wavelet transform?

The Discrete Haar Wavelet transform is a mathematical technique used to decompose a signal into different frequency components. It is based on the Haar wavelet, which is a mathematical function that resembles a square wave.

2. How does the Discrete Haar Wavelet transform work?

The Discrete Haar Wavelet transform works by breaking down a signal into smaller segments and analyzing the differences between adjacent data points. This process is repeated multiple times, resulting in a decomposition of the signal into different frequency components.

3. What are the advantages of using the Discrete Haar Wavelet transform?

The Discrete Haar Wavelet transform has several advantages, including its ability to accurately capture both high and low-frequency components of a signal, its fast computation time, and its ability to represent a signal with a small number of coefficients.

4. How is the Discrete Haar Wavelet transform used in signal reconstruction?

The Discrete Haar Wavelet transform is used in signal reconstruction by first decomposing a signal into its frequency components. The signal can then be reconstructed by using a subset of these components, resulting in a more efficient representation of the signal.

5. What are some applications of the Discrete Haar Wavelet transform?

The Discrete Haar Wavelet transform has many applications, including image and video compression, signal denoising, and feature extraction in data analysis. It is also commonly used in real-time signal processing and data compression for efficient storage and transmission.

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