Blind single-frame deconvolution by tangential iterative projections (TIP)

TL;DR

This paper introduces modifications to the Tangential Iterative Projections (TIP) algorithm, enabling effective single-frame deconvolution, which broadens its applicability in removing optical aberrations from images.

Contribution

The paper presents a novel adaptation of the TIP framework for single-frame deconvolution, expanding its use beyond multi-frame scenarios.

Findings

TIP can be adapted for single-frame deconvolution with modifications.

The single-frame TIP approach improves applicability in various imaging scenarios.

Experimental results demonstrate effective deblurring in single-image cases.

Abstract

Deconvolution serves as a computational means of removing the effect of optical aberrations from recorded images and is employed in many technical and scientific fields of study. In most imaging scenarios the nature of the blurring kernel or point-spread function (PSF) of the imaging system is unknown and both the object and PSF can be estimated using different forms of mathematical optimisation. The Tangential Iterative Projections (TIP) algorithm is a multi-frame deconvolution framework where multiple images can be combined to obtain a single estimate of the object. It is shown here that this framework may be also used for single-frame deconvolution with a few modifications to the algorithm. This step from multiple to one frame is non-trivial and greatly improves the applicability of the TIP framework to most imaging scenarios.