MATLAB Code Implementation for Wavelet Threshold Denoising
- Login to Download
- 1 Credits
Resource Overview
This program performs wavelet threshold denoising with the advantage of automatically determining global threshold size based on the characteristics of 2D data signals, enhancing noise reduction effectiveness.
Detailed Documentation
This wavelet threshold denoising program processes 2D data signals by adapting the global threshold according to signal characteristics, resulting in superior noise removal performance.
The implementation utilizes MATLAB's wavelet transform functions (such as wavedec2 for 2D decomposition) to decompose the signal into multiple resolution levels.
Key algorithmic steps include:
1) Wavelet decomposition using appropriate wavelet bases (e.g., Daubechies or Symlet wavelets)
2) Threshold calculation based on statistical properties of wavelet coefficients (commonly using universal threshold or minimax threshold rules)
3) Threshold application through hard or soft thresholding functions
4) Signal reconstruction via inverse wavelet transform (waverec2 function)
The global threshold determination incorporates signal variance estimation and noise level assessment to optimize denoising for different data types.
- Login to Download
- 1 Credits