Video 13: Image Denoising using Wavelet Transform in Python

March 10, 2021  , ,  No comments




In this video, the wavelet transform based denoising of 2-D signals (Images) is explained using Python. This video includes following components,

  • Denoising scheme using Wavelet Transform.
  • Anaconda and Spyder for Python code development.
  • SciKit-image Python package.
  • Explanation of denoise_wavelet() python function of SciKit-image.
  • Example Python code of denoising of grayscale images.
  • Example Python code of denoising of color images.

Python is a programming language, which is very popular among data scientists and machine learning programmers. This video will help viewers in understanding wavelet transform of 2D signals using Python. Wavelet transform is also a very powerful tool which is widely used for feature extraction and hence finds its importance in the area of machine learning.

Links to previous videos:

1. Introduction to Wavelet Theory and its Applications: Click Here

2. Wavelet Transform based denoising of 1D signals using Python: Click Here​

3. Wavelet Transform Analysis of images using Python: Click Here

Other Links: 

1. Anaconda Distribution Documentation: https://docs.anaconda.com/anaconda/​

2. Anaconda Distribution Packages list: https://docs.anaconda.com/anaconda/packages/py3.7_win-64/

3. Anaconda Distribution Download: https://www.anaconda.com/distribution/​

4. Spyder IDE: https://www.spyder-ide.org/​

5. SciKit Image Documentation: https://scikit-image.org/docs/stable/index.html



Download Resources:

1. Lena Image: Download.
2. Pepper Image: Download.


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