Development and Status of Image Matching in Photogrammetry

Abstract Image and template matching is probably the most important function in digital photogrammetry and also in automated modelling and mapping. Many approaches for matching have evolved over the years, but the problem is still unsolved in general terms. This paper describes the development of image matching techniques in photogrammetry over the past 50 years, addresses the results of some empirical accuracy studies and also provides a critical account of some of the problems that remain. Although automated approaches have quite a number of advantages, the quality of the results is still not satisfactory and, in some cases, far from acceptable. Even with the most advanced techniques, it is not yet possible to achieve the quality of results that a human operator can produce. There is an urgent need for further improvements and innovations, be it through more powerful multi‐sensor approaches, thereby enlarging the information spectrum, and/or through advancements in image understanding algorithms, thus coming closer to human capabilities of reading and understanding image content.