MATLAB Implementation of Image Registration Using Mutual Information

Image registration is a crucial image processing technique that aligns feature points across different images to achieve rotational and translational corrections. In MATLAB implementations, this process typically involves optimizing transformation parameters using mutual information as a similarity metric. The algorithm calculates pixel intensity dependencies between two images through probability density functions, where higher mutual information indicates better alignment. Key MATLAB functions include imregister() for automatic registration and imtransform() for applying geometric transformations. Mutual information proves particularly effective for multimodal registration as it doesn't rely on direct intensity correlations but rather on statistical dependencies. This method significantly enhances registration accuracy and stability by iteratively adjusting parameters like rotation angles (theta) and translation vectors [tx, ty] until optimal alignment is achieved. Such techniques enable precise image analysis in medical imaging and remote sensing applications by ensuring spatial consistency across differently acquired images.