Multifocus image fusion and depth reconstruction

The acquisition of sharp, full-focus images and the restoration of microscopic scenes require complex instrumentation and algorithms. To conveniently obtain the three-dimensional (3-D) structural information of full-focus images and high-quality microscopic scenes, we construct a zoomable 3-D microscope imaging system and propose new image fusion and depth reconstruction algorithms based on this imaging system. The image acquisition environment of the system is analyzed using interference factors such as light transmission variation and jitter, and the corresponding image preprocessing methods are discussed. We combined the new sum-modified-Laplacian (SML) and local band-limited contrast methods, which contain multiple image features but measure the image definition from different angles, then proposed a mixed-contrast factor, and combined it with the SML method to propose an image fusion method. We then proposed a depth reconstruction method based on the structural similarity of multifocus images. For cases where depth reconstruction results in large distortion with high noise, we proposed a depth value restoration method based on anisotropic diffusion to improve the 3-D reconstruction results. Experimental results show that the proposed image fusion and depth reconstruction methods exhibit excellent performance.