Covariance-Driven Mosaic Formation from Sparsely-Overlapping Image Sets with Application to Retinal Image Mosaicing

A new technique is presented for mosaicing sparselyoverlapping image sets, with a target application of assisting the diagnosis and treatment of retinal diseases. The geometric image transformations required to construct the mosaics are estimated by (1) estimating the transformations between as many pairs of images as possible, (2) extracting sets of constraints (correspondences) from the successfully registered image pairs, and (3) using these constraint sets to simultaneously (jointly) estimate the final transformations. Unfortunately, this may not be sufficient to construct seamless mosaics when two images overlap but can not be successfully registered (step 1). This paper presents a new method to generate constraints between such image pairs, and use these constraints to estimate a more consistent set of transformations. For each pair, transformation parameter covariance matrices are computed and used to estimate the mapping error covariance matrices for individual features from o...

• Type: Conference
• Year: 2004
• Where: CVPR
• Authors: Gehua Yang, Charles V. Stewart
• Keywords: Computer Vision, CVPR 2004, Difficult Image Sets, Geometric Image Transformations, Parameter Covariance Matrices, Relevant Image Pairs, Sparselyoverlapping Image Sets