Curvelet Toolbox for Multiscale Image Processing with Ridgelet Transformations
- Login to Download
- 1 Credits
Resource Overview
Detailed Documentation
The Curvelet Toolbox serves as a robust image processing solution that implements ridgelet transformations to extract image edges, perform denoising, and enhance visual quality. Through function calls like fdct_wrapping for fast discrete curvelet transforms, users can achieve superior directional sensitivity compared to wavelet transforms. The toolbox employs multiscale pyramid decomposition and directional filtering algorithms to preserve edge continuity while suppressing noise. Advanced parameter tuning options allow customization of scale/direction parameters via curvelet function arguments. Whether for academic research or industrial applications, the toolbox provides MATLAB-compatible functions such as ifdct_wrapping for inverse transformations, enabling flexible preprocessing pipelines for medical imaging, remote sensing, and computer vision tasks with optimized computational efficiency.
- Login to Download
- 1 Credits