Xie Jing, Hu Yongfu, Tang Qi, et al. Automatic exposure technology for space camera[J]. Opto-Electronic Engineering, 2018, 45(11): 180033. doi: 10.12086/oee.2018.180033
Citation: Xie Jing, Hu Yongfu, Tang Qi, et al. Automatic exposure technology for space camera[J]. Opto-Electronic Engineering, 2018, 45(11): 180033. doi: 10.12086/oee.2018.180033

Automatic exposure technology for space camera

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  • Highly integrated miniature cameras based on CMOS sensors have been used more and more widely in spacecraft. Space camera can accomplish the key operation record, remote sensing and near celestial observation of spacecraft, and has the characteristics of small volume, light weight and intelligent. In order to achieve a good imaging effect, automatic exposure technology which is suitable for the space environment is indispensable. In this paper, a fast adaptive exposure algorithm is proposed for the particularity of space environment and the irreversibility of spatial tasks. The algorithm is based on energy analysis, weighting statistics on the target according to the statistics of the image, and using the lookup table method to calculate the optimal exposure time. The double objective adjustment range is set, so that the automatic exposure algorithm converges better. The experimental results show that the algorithm can obtain the best exposure time quickly and stably. The speed of exposure is fast and the stability is high. It is very suitable for space scene detection. The correlation algorithm has been successfully applied to multiple on orbit models.
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  • Overview: The automatic exposure technology controls the imaging brightness by adjusting the exposure time of thecamera, so that the image is suitable for visual observation. In space field, space camera based on CMOS image sensorhas been widely used for its high integration, small volume and light weight. It plays a very important role in spacecraftkey action records, earth remote sensing and near earth observation. Because of the particularity of space environment, the irreversibility of space tasks and the lag of manual intervention, the camera can be intelligent and autonomous, which is very important. The camera can quickly and automatically adjust the imaging parameters and get the best imaging results for the first time. In view of the particularity of space environment and the irreversibility of space tasks, afast adaptive exposure algorithm is proposed, which can separate the target from the background and adjust the exposure time quickly and steadily. It is very suitable for deep space exploration and remote sensing. First of all, taking theremote sensing image as an example, the imaging link simulation is carried out. Special software is used to analyze theimaging link and get the target radiance. On the basis of the simulation analysis of the imaging link, according to theimaging characteristics of the lens and the sensitivity of the image sensor, the energy of the target to reach the imagesensor and the number of electrons converted from the lens are calculated to estimate the exposure time range, thussetting the initial exposure value. The target and background are separated by simple histogram distribution statistics.The different weights are applied to the target and the background. The luminance characteristics of the image are calculated by the weighted statistics. The exposure time is obtained by the look-up table method according to the result ofthe luminance characteristic. In the process of adjusting the exposure time, a dual target adjustment range is set up tomake the auto exposure algorithm converge well. The algorithm can be conveniently implemented on FPGA with lessresource occupancy and no complex operation. The algorithm is fast in computing speed and large in throughput, andcan be easily transplanted on various platforms. The experimental results show that the algorithm can quickly and stablyobtain the best exposure time, fast convergence speed, high stability, and less resource occupancy, which is very suitablefor space scene detection. The correlation algorithm has been successfully applied to multiple on orbit models, and alarge number of effective images have been obtained.

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