RESULTS: Global Alignment
Attenuation and scattering make image registration difficult and errors in image registration cause misalignment when images are mapped onto a mosaic (e.g. global) frame. Global projection of images (global or absolute homography) can be calculated by multiplying successively homographies between time consecutive images. Since homographies have some errors due to positions of correspondences and estimation method and so on, calculating global homographies from the time consecutive ones, accumulating, makes the error bigger in the form of misalignment and distortions on the mosaic, especially in the last part of the mosaic. To deal with this problem, global alignment methods are needed.


In lack of other sensor data, the motion between time consecutive images is relevant information in order to estimate the topology of a complete sequence and to find the non-time consecutive overlapping images that provide useful information for global alignment. Although local alignment between images might be good, global alignment is still needed due to error propagation. Especially the errors on the estimated motion have to be dealt with when the camera revisits an area that has been already visited. The aim of global alignment is to overcome cumulative error and build a seamless and well aligned mosaic.