The Retinal Image Mosaic Based on Invariant Feature and Hierarchial Transformation Models

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.