Automated Rigid Registration of Two Images

We propose a novel method for fully automated rigid registration of two images. This approach utilizes mixed MATLAB and C++ programming architecture, significantly accelerating processing speed through compiled language optimization. The implementation incorporates key algorithmic improvements including enhanced feature detection algorithms and optimized transformation parameter calculations. Furthermore, we have integrated parallel computing techniques using MATLAB's Parallel Computing Toolbox and C++ multithreading, distributing computational workloads across multiple cores. The system employs a multi-stage registration pipeline: feature extraction using SURF (Speeded-Up Robust Features) algorithm, similarity metric calculation with normalized cross-correlation, and transformation optimization through gradient descent methods. These enhancements enable faster image registration execution, substantially improving overall processing pipeline efficiency while maintaining registration accuracy.