High-quality three-dimensional reconstruction and noise reduction of multifocal images from oversized samples

Abstract

Three-dimensional (3-D) reconstruction is an indispensable tool in areas such as biology, chemistry, medicine, material sciences, etc. The sample can be reconstructed using confocal or nonconfocal mode of a microscope. The limitation of the confocal approach is the sample size. Currently used devices work mostly with sample surface area up to 1 cm2. We suggest a three-step method that creates 3-D reconstruction from multifocal images in nonconfocal mode that is qualitatively comparable to the confocal results. Our method, thus, takes advantage of both microscope modes—high-quality results without sample size limitation. The preprocessing step eliminates the additive noise with Linderberg-Levi theorem. The main focus criterion is based on adjusted Fourier transform. In the final step, we eliminate the defective clusters using the adaptive pixel neighborhood algorithm. We proved the effectiveness of our noise reduction and 3-D reconstruction method by the statistical comparisons; the correlation coefficients average 0.987 for all types of Fourier transforms.