A Research and Strategy of Objection Detection on Remote Sensing Image

Abstract

Data acquisition from satellite is a challenging task due to the limitation of ground station resource and data transmission capacity. Considering that most of the raw data downloaded to the ground are useless, it is worthy to directly get the results by automatic detection on orbit and only transfer the images that include the target objects, which can filter the useless data efficiently. On orbit automatic detection, satellite computing resources need to be considered, so a smaller and faster model needs to be built. Though enormous object detection methods have been proposed and several application have emerged, a detailed survey on different models about detection accuracy and detection speed as well as memory cost is still lacking. This paper aims to provide a survey on the recent object detection researches and make a strategy to detect on orbit. To further compare the performance among different methods, we conduct an experiment in the same real dataset and compare them from accuracy, speed and memory cost. Following the experiment result, a feasible strategy of object detection for the TZ-1 satellite on-orbit which has a low memory dependency, fast speed and comparable accuracy adapt to its computing resources is proposed.