Abstract

Abstract. UAVs (Unmanned aerial Vehicles) can acquire images easily without large cost. For this reason, use of UAV is spreading to diverse fields such as orthoimages and DEM/DSM production. The spatial resolution of images is usually expressed as a GSD (Ground Sampling Distance). The GSD from UAV has higher performance than other platforms such as satellites and aircraft because it shoot at low altitude. However, blurring and noise may occur on UAV images due to the weather and the stability of UAV. However, since the GSD from UAV cannot sufficiently meet the spatial resolving power of the actual image system, a criterion for determining the spatial resolution of image is needed. Therefore we emphasize that the quality of the image needs to be analysed. Actual performance indicators such as GRD (Ground Resolved Distance) and NIIRS (National Image Interpretability Rating Scales), which can be measured through image analysis, are representative examples of image quality interpretation. It is possible to extract NIIRS form image quality related parameters such as MTF (Modulation Transfer Function), RER (Relative Edge Response) and SNR (Signal to Noise Ratio). In this paper, we aim to apply the Edge analysis method to UAV and to analyse the result. The analysis result showed that while GSD and NIIRS were highly dependent to imaging altitude, GRD and image sharpness showed optimal altitude ranges. The exact optimal range varied between images taken at different weather conditions. While we need a further study, this may indicate that edge analysis may provide an optimal operational altitude range suitable for the sensors.

Highlights

  • Along with the development of optical systems, various types of images are actively being distributed through various platforms such as aerial, satellite and UAVs (Unmanned aerial Vehicles)

  • The edge analysis method originally developed for satellite image was applied to UAV image to analyze image quality

  • RER, SNR, MTF, NIIRS and GRD image quality parameters were calculated from artificial targets using self-developed software (Kim et al, 2010; Kim et al, 2011)

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Summary

Introduction

Along with the development of optical systems, various types of images are actively being distributed through various platforms such as aerial, satellite and UAVs (Unmanned aerial Vehicles). Techniques for extracting and utilizing various information using various are developing, and a need for a scale for judging the quality of the image is emphasized. UAV can acquire high quality images with high spatial resolution. For this reason, UAV are being used in various fields such as construction, agriculture, forestry, and disaster. In case when the image of the UAV is unclear about the image quality, acquisition and mapping of accurate three-dimensional information have a great influence on the work

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