Digital refocusing of images recorded with white light using Lucy-Richardson-Rosen algorithm

Abstract

Lens-based imaging is one of the widely used scientific methods to record optical information. As long as the imaging conditions are satisfied, this method can be used to image an object faithfully. However, beyond the limit of the depth of focus of the optical element, the collected image appears blurred. Though shifting the location of the optical element or the sensor offers a solution to the above problem, it is not suitable for recording dynamic events. There are different deconvolution methods available for digital refocusing of blurred images. Recently, a new reconstruction method called Lucy-Richardson-Rosen algorithm (LR2A) was developed for deconvolution based 2D and 3D incoherent imaging applications. In the present work, we have demonstrated LR2A on blurred images recorded using white light for the first time. A simple, commonly available refractive lens along with an incoherent white light source was used to record the point spread functions (PSF) at different depths. Then, the object information in the corresponding planes were also recorded. Finally, the PSF library was used to digitally refocus the object information. The results were compared with standard algorithms such as Lucy-Richardson and nonlinear reconstruction methods. In all the cases, LR2A exhibited a superior performance.