Illumination correction in dermatological photographs using multi-stage illumination modeling for skin lesion analysis.
A novel algorithm for correcting illumination variation in dermatological photographs via a multi-stage modeling of the underlying illumination is proposed for the purpose of skin lesion analysis. First, an initial illumination estimate is obtained via a non-parametric modeling strategy based on Monte Carlo sampling. Next, a subset of pixels from the non-parametric estimate is used to determine a parametric estimate of the illumination based on a quadratic surface model. Using the parametric illumination estimate, the reflectance map is obtained and used to correct the photograph. The photographs corrected using the proposed algorithm are compared to uncorrected photographs and to a state-of-the-art correction algorithm. Qualitatively, a visual comparison is performed, while quantitatively, the coefficient of variation of skin pixel intensities is calculated and the precision-recall curve for segmentation of skin lesions is graphed. Results show that the proposed algorithm has a lower coefficient of variation and an improved precision-recall curve.
Vision and Image Processing Lab with the Department of Systems Design Engineering, University of Waterloo, Ontario, Canada. jlglaist@uwaterloo.ca
Jeffrey
J
Glaister
Alexander
A
Wong
David A
DA
Clausi
D000465:Algorithms; D016208:Databases, Factual; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D008297:Male; D012815:Signal Processing, Computer-Assisted; D012867:Skin / Q000473:pathology*; D012871:Skin Diseases / Q000473:pathology*