compositional algorithm the weights must be constant and they must be chosen prior to the computation of the steepest descent images i e they must be based off features of the virtual images taking advantage of the equivalence of normalized ssd and normalized cross correlation the update can be found as is the set of mean subtracted steepest descent images divided by the variance of the virtual image i v and u012b i i are the normalized images to validate the algorithm sample results for the virtual to real and virtual to virtual registration cases are given in both of the cases outlined below the virtual environment is a ct chest scan of a human patient designated h005 the airway surfaces were automatically generated using the methods of kiraly et al 10 airway centerlines were extracted using the methods of swift et al and the virtual viewing sites were chosen along these airway centerlines at intervals varying between 0 3 mm and 1 mm with the viewing direction chosen parallel to the airway centerline 11 virtual images and depth maps were generated by an opengl renderer assuming a spot light source at the camera focal point a field of view of 78 2 degrees and a 264 u00d7 264 image size to match the calibration parameters of the bronchoscope camera the virtual to real registration was performed using pyramid decomposition starting from level 3 and ending at level 1 to account for the difference in intensity characteristics between the imaging sources the weighted normalized cross correlation 12 was used as the objective function with weights w u v chosen as in order to emphasize dark areas which tend to have more information in bronchoscopic video the video frame.