Joint optimization of spatial registration and histogram compensation for microscopic images.
An iterative registration algorithm, the Lucas-Kanade algorithm, is combined with the histogram transformation to jointly optimize the spatial registration and the histogram compensation. Based on a simple regression model, a nonparametric estimator, the empirical conditional mean, is used for the histogram transformation function. The proposed algorithm provides a good performance in registering microscopic images that have different exposure or histogram properties, and can easily adopt other histogram compensation schemes and variations of the Lucas-Kanade algorithms due to its implicit flexibility. Joint registration with a third-order polynomial warp and compensation is conducted for microscopic images that have different magnifications.
Kim
Dong Sik
DS
Sch. of Electron. & Inf. Eng., Hankuk Univ. of Foreign Studies, Korea.
Lee
Kiryung
K
Lee
Kyung Eum
KE
Han
Sung Sik
SS
D000465:Algorithms; D007091:Image Processing, Computer-Assisted; D008854:Microscopy, Electron; D015233:Models, Statistical; D012044:Regression Analysis; D013223:Statistics as Topic; D018709:Statistics, Nonparametric