Background normalization is a low-level image processing task typically used to enhance images by eliminating featureless, nonuniform background illumination. Automatic background normalization requires three distinct steps: threshold selection and segmentation, reconstruction of background image, and subtraction. This paper presents a new region-based thresholding criterion for background identification and normalization. Experimental results will be presented.
"Iterated facet model approach to background normalization", Proc. SPIE 2238, Hybrid Image and Signal Processing IV, (1 June 1994); doi: 10.1117/12.177715; https://doi.org/10.1117/12.177715