Luminosity and contrast normalization in retinal images

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Robust Retinal Vessel Segmentation via Locally Adaptive Derivative Frames in Orientation Scores (2016, methodology): “[29] is employed to obtain a uniform illumination distribution.”
Automatic detection of microaneurysms in color fundus images (2007, background): “A more general approach for retinal image normalization based on background detection has been proposed in [8] and [9]; it would be interesting to study the influence of these advanced image normalization techniques on the MA detection performance.”
Automated microaneurysm detection using local contrast normalization and local vessel detection (2006, methodology): “Another contrast normalization method is described by Foracchia et al. [ 10 ].”
Retinal Blood Vessel Segmentation Using Line Operators and Support Vector Classification (2007, methodology): “9419 (49 49 window), while using the method of [28] the maximum accuracy was 0.”
Automatic Diabetic Macular Edema Detection in Fundus Images Using Publicly Available Datasets (2011, background): “, 2006) and has considerable computation performance advantages over other methods (Foracchia et al., 2005).”