Explore MATLAB source code curated for "小波分解" with clean implementations, documentation, and examples.
Image fusion technique combining features from two images through wavelet decomposition and multiple fusion methods, with code implementation details for wavelet transformation and fusion algorithms.
This project utilizes MATLAB to implement an image digital watermarking algorithm based on wavelet decomposition combined with Arnold transform, which has been successfully debugged and verified. The implementation involves Arnold transformation for image preprocessing, wavelet decomposition for frequency domain analysis, and controlled watermark embedding in wavelet coefficients.
EEG signal waveform analysis involving wavelet decomposition and visualization through plotting
This MATLAB-based image denoising program utilizes wavelet packet decomposition with default thresholding, wavelet decomposition, and reconstruction techniques for effective noise removal.
Perform multi-level wavelet decomposition on images b1 and b2 using the wavedec2() function with 'db1' wavelet at level 3, followed by image fusion implementation.
Step-by-step procedures for wavelet analysis of signals including wavelet decomposition, wavelet reconstruction, and wavelet-based filtering methods with code implementation details.
Implementation of two-level wavelet decomposition for facial images using MATLAB, which generates decomposition diagrams for analysis. Users can simply modify the image filename in the code to process their own images.
This method involves partitioning the image into blocks and performing wavelet decomposition to obtain low-frequency and high-frequency components. It calculates the contrast for each block to classify them into clear blocks and blurred blocks, with adjacent areas between clear and blurred blocks defined as boundary regions. During fusion, clear blocks are directly selected as the corresponding fused blocks. For boundary regions, a contrast-based pixel selection method is applied on the wavelet decomposition basis, implementing weighted fusion algorithms to optimize edge transitions and enhance image clarity.
Four-Level Wavelet Decomposition for EEG Signals - This program implements a four-layer wavelet decomposition algorithm for EEG signal processing, accompanied by comprehensive MATLAB programming course materials designed to facilitate understanding of wavelet-based signal analysis techniques.
An illustrative example of wavelet decomposition and reconstruction suitable for time series analysis and prediction, including implementation approaches!