Textured digital elevation models (TDEMs) have valuable use in precision agriculture, situational awareness, and disaster response. However, Scientific-quality models are expensive to obtain using conventional aircraft-based methods. Photogrammetry-based techniques have no direct measurements, and thus has uncertainty in the reconstruction. The concept of a texel camera, which has both aerial imagery and ladar measurements from an inexpensive small UAV, can be used to combine the two methods. A texel camera fuses calibrated ladar measurements and electro-optical imagery upon simultaneous capture, creating a texel image. This eliminates the problem of fusing the data in a post-processing step and enables both 2D- and 3D-image registration techniques to be used. A texel camera outputs texel swaths during a UAV flight. A swath consists of an aerial image that is calibrated to associated depth measurements. This thesis describes an automatic algorithm for registering these texel swaths into a TDEM. The algorithm involves image processing, 3D geometry, and nonlinear optimization processes. The algorithm is seeded with a coarse estimate of the position and attitude of each texel swath capture, obtained using an on-board navigation system. Analysis of several data sets registered using this algorithm is shown. This method enables an inexpensive alternative to obtaining high quality textured 3D landscapes.