A phase congruency-based green fluorescent protein and phase contrast image fusion method in nonsubsampled shearlet transform domain.

Abstract

Image fusion technique is an effective way to merge the information contained in different imaging modalities by generating a more informative composite image. Fusion of green fluorescent protein (GFP) and phase contrast images is of great significance to the subcellular localization, the functional analysis of protein, and the expression of gene. In this article, a phase congruency (PC)-based GFP and phase contrast image fusion method in nonsubsampled shearlet transform (NSST) domain is presented. The input images are decomposed by the NSST to acquire the multiscale and multidirection representations. The high-frequency coefficients are fused with a strategy based on PC and parameter-adaptive pulse coupled neural network (PA-PCNN), while the low-frequency coefficients are integrated through a local energy (LE)-based rule. Finally, the fused image is generated by conducting the inverse NSST on the merged high- and low-frequency coefficients. Experimental results illustrate that the presented method outperforms several state-of-the-art GFP and phase contrast image fusion algorithms on both qualitative and quantitative assessments.