Quantitative phase estimation in 2D optical diffraction imaging using iterative blind deconvolution

Optical diffractive imaging presents a useful framework for the quantitative estimation of refractive index distribution from the measured diffracted field data of transparent objects. Reconstructing the complex refractive index distribution from noisy diffracted field data is often ill-posed. Traditional reconstruction approaches involve assumptions about the optical system or objects, restricting their application to real-world scenarios. This paper presents an iterative blind deconvolution with TV regularization for optical diffractive imaging reconstruction. Our method estimates the refractive index distribution and point spread function (PSF) simultaneously, compensating for unknown aberrations and system imperfections. Extensive simulations and experimental results demonstrate the superiority of the proposed method over extensive algorithms, which are based on iterative reconstruction based on state-of-the-art methods like the FISTA forward-backward splitting method governed by the exact solution of the Lippmann-Schwinger equation. equation.