Levenberg-Marquardt and Line-Search Extended Kalman Smoothers

The aim of this article is to present Levenberg–Marquardt and line-search extensions of the classical iterated extended Kalman smoother (IEKS) which has previously been shown to be equivalent to the Gauss–Newton method. The algo- rithms are derived by rewriting the algorithm’s steps in forms that can be efficiently implemented using modified EKS iter- ations. The resulting algorithms are experimentally shown to have superior convergence properties over the classical IEKS

Blending techniques for underwater photomosaics

The creation of consistent underwater photomosaics is typically hampered by local misalignments and inhomogeneous illumination of the image frames, which introduce visible seams that complicate post processing of the mosaics for object recognition and shape extraction. In this thesis, methods are proposed to improve blending techniques for underwater photomosaics and the results are compared with traditional methods. Five specific techniques drawn from various areas of image processing, computer vision, and computer graphics have been tested: illumination correction based on the median mosaic, thin plate spline warping, perspective warping, graph-cut applied in the gradient domain and in the wavelet domain. A combination of the first two methods yields globally homogeneous underwater photomosaics with preserved continuous features. Further improvements are obtained with the graph-cut technique applied in the spatial domain