Joint optimization of spatial registration and histogram compensation for microscopic images.

Dong Sik Kim, Kiryung Lee, Kyung Eum Lee, Sung Sik Han

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

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.

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

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