Multifocus Microscopy Image Fusion Based on Background Optimization and Edge Enhancement

The depth of field limitations of the microscope optical system make it impossible for a single image to clearly represent the structure of the sample at different depths simultaneously. While multifocal fusion integrates sharp areas from multiple focal planes to achieve wide-field high-resolution imaging, current methods have edge artifacts due to poor background suppression and inadequate edge enhancement. To effectively alleviate this key challenge, a multifocal micro-image fusion method based on background optimization and edge enhancement is proposed. The method first performs saturation-based background optimization processing on microscopic images, and then uses an edge enhancement algorithm and an adjacency filter to extract the decision maps and infographics corresponding to the structural layer and detail layer, respectively. Experimental results show that the proposed method has significant advantages in subjective and quantitative evaluation, and can improve edge information transfer (Q^AB/F) by up to 30% while reducing edge artifacts.