Image Fusion Method Using Local Energy Maximum Selection Rule

Image fusion serves as a prominent research area within image processing, and this implementation demonstrates the Local Energy Maximum Selection Rule fusion technique. Image fusion involves the process of integrating multiple source images into a single composite image to extract shared features and information from each input. This technology finds extensive applications across computer vision, medical imaging, remote sensing, and related domains. The Local Energy Maximum Selection Rule constitutes a widely adopted image fusion methodology that determines pixel selection based on energy distribution patterns within images, thereby achieving superior fusion outcomes. Implementation typically involves calculating local energy maps using convolution operations with specific filters or window functions, followed by pixel-wise selection where the maximum energy value determines the final composite pixel. Consequently, this method garners significant attention in the image processing field and sees broad adoption in practical applications due to its effectiveness in preserving salient features while minimizing artifacts.