Phase Difference Algorithm Based on Blind Deconvolution with Image Restoration
- Login to Download
- 1 Credits
Resource Overview
A blind deconvolution-based phase difference algorithm for image restoration, including simulation implementations and L-BFGS optimization algorithm with code demonstrations
Detailed Documentation
Building upon the foundation of blind deconvolution-based phase difference algorithms, we propose a novel image restoration approach. This method integrates simulation techniques with the Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) optimization algorithm to enhance both restoration quality and computational efficiency. The implementation features gradient-based optimization with Hessian approximation for efficient convergence. The package includes detailed simulation results demonstrating point spread function estimation and phase retrieval processes, along with complete code implementation of the optimization workflow. These resources provide practical insights for understanding and applying the methodology, enabling superior image restoration outcomes through proper parameter tuning and algorithm configuration.
- Login to Download
- 1 Credits