Shearlet Transform Toolkit

The shearlet transform package serves as a powerful image processing toolkit. It contains demonstrative examples that can be applied to various image processing tasks such as image denoising and image fusion. The implementation employs directional multi-scale analysis through shearlet systems, which provide optimally sparse representations for multidimensional data. By utilizing this package, you can efficiently perform detailed image processing and optimization. The denoising algorithm leverages thresholding techniques in shearlet domains, while the fusion method combines directional features from multiple images through coefficient selection rules. Whether you need to remove noise artifacts or merge multiple images into a single composite, this shearlet transform package provides effective mathematical frameworks and corresponding MATLAB/Python implementation examples. Key functions include directional filtering, multi-resolution decomposition, and inverse transform reconstruction. Try it now to explore advanced image processing capabilities!