Locating Control Points In Aerial Images With A Multi‐Scale Approach Based On Terrestrial Image Patches

Abstract

The objective of the proposed approach is to locate and measure ground control points in aerial images when large image search spaces are defined due to the use of inaccurate initial exterior orientation parameters, such as those provided by consumer-grade navigation systems. Vertical terrestrial image patches covering control point areas are generated and compared with aerial patches using feature-and area-based matching algorithms to automatically determine their corresponding positions in aerial images with sub-pixel precision. The approach is based on techniques for both image search space reduction and adaptive least squares matching. Experiments with real data were performed with bundle block triangulation and the results were analysed using control and check points in both object and image spaces. The proposed technique enabled a significant reduction in the search space within which it was feasible to successfully locate control points. Compared with manual measurements, the results obtained by the automatic technique were more accurate, achieving one-fifth of the ground sample distance in planimetric check point discrepancies.

Automatic Measurement of Control Points for Aerial Image Orientation

“…A previous paper already showed the potential of this concept (Berveglieri and Tommaselli, ) but still had some manual steps. Distinguishable features surrounding a surveyed GNSS point enable identification of its measurement in an aerial patch with sub‐pixel precision, as shown in Fig.…”

“…Developing techniques to automatically measure control points in aerial and satellite images has attracted many researchers, both to reduce the time needed for manual identification and measurement and to reduce the subjective judgement of the human operator when measuring an image. This paper builds on a technique previously published (Berveglieri and Tommaselli, ), making it fully automatic and more accurate. This development is based on the recognised need for more efficient and accurate techniques for determination of photogrammetric exterior orientation.…”

“…The approach proposed in this paper uses terrestrial image patches as control entities, and removes some restrictions of the original technique as presented by Berveglieri and Tommaselli (), in which these image patches were collected to be matched with aerial images, as depicted in Fig. .…”

Accuracy Analysis of Control Point Distribution for Different Terrain Types on Photogrammetric Block

“…However the results obtained present systematic errors [24]. In order to evaluate the accuracy or quality of a block adjustment and eliminate the systematic errors therein, the ground control points within the object space are required to be established [3].The studies thus far conducted seem to suggest that the systematic errors can be eliminated by correcting the navigation sensors -GPS/INS, calibration, datum or projection details and by introducing ground control points that are distributed within the block in a geometrically consistent fashion [22,27,21,3]. Aerial triangulation networks are a sum total of mostly large and irregular shaped different geometrical blocks that consist of different flight configurations.…”

Position estimation of mobile mapping imaging sensors using aerial imagery

“…The registration of the data sets is, however, a challenging task due to the overall differences between the image data sets. In current literature, registration approaches rely on aerial nadir images which entail the identification of mostly ground-based features that are salient in both data sets, such as road markings (Azimi et al, 2018;Berveglieri and Tommaselli, 2015;Fischer et al, 2018;Javanmardi et al, 2017). Despite the high accuracy which is potentially achievable with these methods, groundbased features may be occluded in the aerial nadir image or not even present in certain areas.…”