True Ortho Processing
Flight Planning and “Managed Mosaicking”
These two methods both have pro's and cons and are more applicable in some circumstances rather than others.
The first method refers to special techniques used to create true orthos. The ortho photography page at Eastern Topographics outlines the pre and post-processing results quite well. The technique that is typically applied involves the use of input images and a bare-earth terrain model (just like regular ortho processing), but with an additional component of 3D building features that need to be captured in stereo via a 3D feature extraction software. So the raw ingredients to the process would be (a) input imagery, (b) bare earth terrain, and (c) 3D feature data. It is the latter component that typically drives up the cost of production. Because the buildings are typically extracted manually, the human cost of collection gets bundled into the true ortho pricing. As for what actually goes on in the processing, a comment on the previous post provided an excellent link to explain the details of automated true ortho processing. It also outlines the importance of color matching, which is important for achieving acceptable results. The other thing to keep in mind is to ensure there is enough valid pixel data, otherwise occluded areas (aka the areas of the image obscured by building lean) in the input imagery may be filled with black void pixels. This can be alleviated by ensuring the imagery was collected with a high enough overlap percentage.
The other method that is often employed is to simply fly the project area with a very high degree of overlap (e.g. 80/80 forward/sidelap versus the usual 60/40). Then orthos are produced for all the frames via the usual approach with bare earth terrain. During the mosaick process, the operator can then interactively select the image portions (the center area of each frame) via seam editing, mosaick the images and then tile them back out into whatever their specification requirement calls for. This approach may not be applicable for high urban environments (e.g. Manhattan) but can work well for suburban and low-rise building with a few high-rises here and there. While fuel costs are going to be higher because of the increases overlap, the processing costs should remain low.
Note that pushbroom sensors such as the ADS80 can be ideal for the latter approach. This is because they can capture imagery at nadir in long strips, which dramatically reduces the number of input images into the mosaic process. Here's a screen capture of ADS80 imagery taken from the middle of the strip. While the multi-story buildings along the edges of the strip have discernible building lean, the imagery at the center doesn't show any. Flying with high sidelap would allow for the inclusion of just the central areas for the mosaic processing. It may not be perfect 100% of the time, but I would argue that it is good enough for many applications, without requiring the high cost of collecting all the building features.