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AugeLab Studio Manual
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Wavelet Transforms

Wavelet Transforms Node Documentation

The Wavelet Transforms node in AugeLab Studio applies wavelet transforms to an input grayscale image.

Node Overview

The Wavelet Transforms node applies wavelet transforms to an input grayscale image. Wavelet transforms are used for multi-resolution analysis of signals or images, decomposing them into different frequency components.

Node Properties

  • Node Title: Wavelet Transforms
  • Node ID: OP_NODE_WAVELET

Inputs

The Wavelet Transforms node has the following input socket:
  • ImageGray: The input grayscale image to be transformed.

Outputs

The Wavelet Transforms node has the following output socket:
  • ImageGray: The transformed image after applying wavelet transforms.

Node Configuration

The Wavelet Transforms node allows you to configure the following parameters:
  • Wavelet Type: Select the type of wavelet to be used for the transforms. The available wavelet types are: haar, db1, sym2, coif1, bior1.3, rbio1.3, and dmey.
  • Wavelet Level: Adjust the level of wavelet decomposition to control the amount of detail in the transformed image.

Usage

  1. 1.
    Drag and drop the Wavelet Transforms node from the node library onto the canvas in AugeLab Studio.
  2. 2.
    Connect the input grayscale image to the ImageGray input socket of the Wavelet Transforms node.
  3. 3.
    Adjust the wavelet type and wavelet level parameters according to your requirements.
  4. 4.
    Run the pipeline.
  5. 5.
    The Wavelet Transforms node will apply wavelet transforms to the input grayscale image, decomposing it into different frequency components.
  6. 6.
    Retrieve the transformed image from the ImageGray output socket for further processing or visualization.

Notes

  • The Wavelet Transforms node is commonly used for image processing tasks such as denoising, compression, and feature extraction.
  • Different wavelet types and wavelet levels can be chosen to achieve specific analysis goals.
  • The output transformed image will contain different frequency components represented by wavelet coefficients.
  • The transformed image can be further processed using other image processing techniques or nodes in the AugeLab Studio.
  • Experiment with different wavelet types and levels to achieve the desired analysis results.
That concludes the documentation for the Wavelet Transforms node in AugeLab Studio. This node allows you to apply wavelet transforms to an input grayscale image, decomposing it into different frequency components.