The narrow-angle camera (NAC) of the lunar reconnaissance orbiter camera (LROC) uses a pair of closely attached pushbroom sensors, NAC Left (NAC-L) and NAC Right (NAC-R), to obtain a large swath of coverage while providing high-resolution imaging. However, the two image sensors do not share the same lens and cannot be modeled geometrically with a single physical model. This leads to problems in the generation of precision lunar topographic models from NAC images, e.g., the boresight misalignment between NAC-L and NAC-R, and the geometrical inconsistencies for the NACs in different tracks and multiple stereo models due to the irregular overlapping areas. Aiming at solving these problems, this chapter presents a rigorous photogrammetric processing method for NAC images, which consists of three major steps. First, using triple-matching tie points between the NAC images, the boresight offsets are improved through a least-squares adjustment. Then, with the initial estimation provided by the calibrated boresight angles, the orientation parameters of a stereo pair of NAC images are further refined through a combined block adjustment. In addition, in order to reduce the number of stereo models, we propose a coupled epipolar rectification method, which merges the NAC-L and NAC-R in the disparity space. Finally, dense matching by a semi-global matching method produces a pixelwise disparity map, from which the high-resolution lunar topographic model can be derived. Experimental results reveal that the presented approach is able to reduce the gaps and inconsistencies caused by the inaccurate boresight offsets between the two NAC cameras and the irregular overlapping regions, and to finally generate precise and consistent 3D topographic models from the NAC stereo images. This chapter presents an automatic and rigorous photogrammetric processing pipeline of narrow-angle camera (NAC) images for precision and high-resolution lunar topographic mapping. It discusses the related works on lunar topographic mapping. The chapter also presents methods to estimate the boresight offsets of the NAC images and block adjustment and coupled rectification for NAC images, which reduces the stereo models by merging NAC-L and NAC-R in the epipolar space. It describes the dense image matching methods using the texture-aware semi-global matching. The chapter provides an effective photogrammetric processing pipeline for precision and high-resolution topographic mapping using Lunar Reconnaissance Orbiter Camera NAC images. After the boresight calibration as described, the intra-track inconsistencies of NAC images will reduce. The approach and the generated results can also be used in a variety of applications, such as landing site mapping and selection, rover maneuvering, and geological analyses of the lunar surface that require high-quality topographic data.