Abstract. In recent years, Unmanned Aerial Vehicles (UAVs) have become popular tools in mapping applications. In such applications, the image motion, bad lighting effects, and poor texture all directly affect the quality of the derived tie points, which in turn imposes constraints on image extraction and may lead to a low accuracy point cloud. This paper proposes a contrast enhancement technique to improve the accuracy of a photogrammetric model created using UAV images. The luminance component (Y) in the YIQ color space is normalized using the sigmoid function, and the low contrast images are enhanced using the Contrast-Limited Adaptive Histogram Equalization (CLAHE) on the luminosity component. To evaluate the proposed method, three-dimensional models were created using images acquired by the Phantom 4 Pro UAV in three distinct places and at altitudes of 20, 40, 60, 80, and 90 meters. The results showed that enhancing the contrast of images increased the number of tie points and reduced reprojection error by approximately 10%. It also improved the resolution of the digital elevation model by approximately 2cm/pixel while greatly improving the texture and quality with respect to that developed using the original images.

Abstract. In recent years, as the use of Unmanned Aerial Vehicle (UAV) imaging systems has increased, the photogrammetry community has conducted extensive research on the unique advantages of these systems. The UAVs are considered as one of the most important platforms for photogrammetry applications from various urban and non-urban areas at different scales. In UAV photogrammetry projects the spatial resolution of the images must be determined prior to the imaging stage. The spatial resolution of the images is a commonly-used criterion for detecting the smallest distance between two adjacent separable objects in the images. Numerous methods have been developed to precisely evaluate the spatial resolution of images. In this study, the Siemens star target, which is one of the most commonly used artificial targets for analysing spatial resolution was studied. The objective of this paper is to evaluate and compare the reduction of spatial resolution coefficient using the Siemens star target in images captured by UAVs. To this end, a method for automatically detecting the radius of the circle of ambiguity and calculating spatial resolution in UAV images has been developed. According to the findings of this study, the initial step in creating the Siemens star target, in terms of size and the number of acceptable arms, is dependent on the flying altitude of the UAV and the level of image blur. In addition, the reduction in spatial resolution of images captured by various UAVs varies, and its coefficient must be calculated for each project.