Correction of uneven illumination in microscopic image through robust brightness distribution estimation and deviation rectification

Abstract

For diagnostic purposes, the automatic microscopic scanning system can scan and stitch multiple slide images together to produce a Whole Slide Image. This process provides a clear, high-resolution picture of the slide sample under the high-power objective lens of the microscope, enabling accurate diagnosis and analysis. However, uneven illumination affects every image acquired by a microscope, resulting in the existence of artifacts. In this paper, a novel retrospective approach based on robust brightness distribution estimation and deviation rectification is proposed. Least squares estimation and Cauchy estimation with a smooth regularization term are used to obtain the accurate estimation of background illumination distribution. Then the deviation map is given based on the deviation function of the two directions for illumination correction. This method leverages the statistical properties of image sequences to enhance stability and robustness against biological image artifacts. Through experimental validation, this approach successfully eliminates visible edge artifacts that commonly appear between neighboring tiles and exhibits superior performance when compared to other methods.