Blind blur assessment for vision-based applications

In this paper, a criterion for objective defocus blur measurement is theoretically derived from one image. The essential idea is to estimate the point spread function (PSF) from the line spread function (LSF), whereas the LSF is constructed from edge information. It is proven that an edge point corresponds to the local maximal gradient in a blurred image, and therefore edges can be extracted from blurred images by conventional edge detectors. To achieve high accuracy, local Radon transform is implemented and a number of LSFs are extracted from each edge. The experimental results on a variety of synthetic and real blurred images validate the proposed method. The algorithm can be implemented for image quality evaluation in vision-based applications as no reference images are needed.