Video 48: Denoising of Signals and Images using Wavelet Packet Transform

 

Hello Viewers, in this video, denoising of signals and images using Wavelet Packet Transform (WPT) is explained.

This tutorial explains the basic theoretical background of WPT based denoising scheme, noise variance estimation and universal threshold calculation. The denoising is implemented in MATLAB to do experiments with different noisy 1D and 2D signals. The concept of full tree and best tree based decomposition is also included.

This video includes following contents:

• Introduction to Wavelet Packet Transform (WPT).
• Objective and Noise Model.
• WPT based Denoising scheme.
• Noise variance estimation and finding universal threshold.
• Thresholding methods.
• MATLAB functions for WPT and WPT based denoising.
• MATLAB code for denoising 1D signals (Audio).
• MATLAB code for denoising 2D signals (Images).

Link for previous videos,

1. Introduction to wavelet theory and Its applications: Click Here

2. Wavelet Packet Transform of Signals and Images: Click here

3. Wavelet based denoising of audio signals using MATLAB & Simulink: Click Here

4. Wavelet based denoising of images using MATLAB: Click Here

Download Resources: 

1. Test Images: Download 

2. Test Audio Clips: Download