Nanoscale depth reconstruction from defocus: within an optical diffraction model

Abstract

Depth from defocus (DFD) based on optical methods is an effective method for depth reconstruction from 2D optical images. However, due to optical diffraction, optical path deviation occurs, which results in blurring imaging. Blurring, in turn, results in inaccurate depth reconstructions using DFD. In this paper, a nanoscale depth reconstruction method using defocus with optical diffraction is proposed. A blurring model is proposed by considering optical diffraction, leading to a much higher accuracy in depth reconstruction. Firstly, Fresnel diffraction in an optical system is analyzed, and a relationship between intensity distribution and depth information is developed. Secondly, a blurring imaging model with relative blurring and heat diffusion is developed through curving fitting of a numerical model. In this way, a new DFD method with optical diffraction is proposed. Finally, experimental results show that this new algorithm is more effective for depth reconstruction on the nanoscale.

Shape reconstruction within an optical diffusion model

“…When the distance map Z is an equifocal plane, the PSF is approximated by a shift-invariant Gaussian, the image model in (2) can be formulated in terms of heat equation [11][12][13] ,…”

“…Equation (18) is a dynamic optimization which can be solved by the gradient flow, the algorithm can be divided into the following steps [11][12][13] , (1). Give camera parameters f, γ, v; set up the iteration parameters: a chosen threshold ε, regularization parameter α and step size β; (2).…”