Illumination field estimation through background detection in optical microscopy

Automated microscopic image analysis techniques are increasingly gaining attention in the field of biological imaging. The success of these applications mostly depends on the earlier image processing steps applied to the acquired images, aiming at enhancing image content while performing noise and artifacts removal. One such artifact is the vignetting effect that in general occurs in most imaging sensors due to an uneven illumination of the scene being imaged. As a consequence, images are usually lighter near the optical center and darker at image borders. This effect is particularly evident when stitching images into a mosaic in order to increase the field of view of the microscope. The existing approaches deal with either the parametric model of the known light distribution or the estimation of the illumination field based on just one image or a sequence of empty-field images. These approaches are only feasible when the acquisition apparatus is at one's disposal. We propose a non parametric and general purpose approach, without using prior information about the light distribution, where the illumination field is estimated from the background, that is built automatically stemming from a sequence of images containing even the objects of interest.