A Review of True Orthophoto Rectification Algorithms

Abstract

Orthophoto is one of the most important basic geographic information products. Because traditional orthophotos use incomplete surface information for digital differential rectification, there is mutual occlusion between images, which is difficult to meet the current large-scale urban mapping requirements. With the rapid development of photogrammetry technology and the increasing demand for high-precision graphics, the true orthophoto has become a major research hotspot at home and abroad. This paper expounds the development of the true orthophoto rectification, summarizes the relevant algorithms for the true orthophoto production, and points out the core problems and future development of the true orthophoto production. Through the summary and analysis of the image rectification algorithm, the image occlusion detection, shadow compensation and other issues are proposed. The morphological filtering algorithm is used to identify buildings in densely populated areas, and the PCNN model method enhances texture features, and combing the deep learning for shadow compensation, in order to optimize the actual image rectification algorithm for existing images.