The Retinal Image Mosaic Based on Invariant Feature and Hierarchial Transformation Models
Lifang Wei, LinLin Huang, Lin Pan, Lun Yu · 2009
It is important to determine the stable keypoints and select transformation models for image registration and mosaic. In this paper a method is presented for retinal image mosaic. Central to the new method is to detect the PCA-SIFT (principal components analysis-scale invariant feature transform) feature and estimate the quadratic transformation model which is employed to simulate the anatomy of human eyes. The transformations models are estimated by matching PCA-SIFT landmarks. The hierarchical notion is used to map the inter-image. The random sample consensus (RANSAC) is used to estimate the affine transformation model and remove exterior point. The quadratic is estimated by m-estimator. And the weighted mean is used to stitch retinal images. The proposed approach can effectively realize the retinal image mosaic.