Auto Exposure Algorithm for Aerial Camera Based on Histogram Statistics Method

SHEN Xiaohe; LIU Jinghong; CHU Guangsheng

doi:10.11999/JEIT150530

Volume 38 Issue 3

Mar. 2016

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Article Navigation > Journal of Electronics & Information Technology > 2016 > 38(3): 541-548

SHEN Xiaohe, LIU Jinghong, CHU Guangsheng. Auto Exposure Algorithm for Aerial Camera Based on Histogram Statistics Method[J]. Journal of Electronics & Information Technology, 2016, 38(3): 541-548. doi: 10.11999/JEIT150530

Citation:

SHEN Xiaohe, LIU Jinghong, CHU Guangsheng. Auto Exposure Algorithm for Aerial Camera Based on Histogram Statistics Method[J]. Journal of Electronics & Information Technology, 2016, 38(3): 541-548. doi: 10.11999/JEIT150530

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Auto Exposure Algorithm for Aerial Camera Based on Histogram Statistics Method

doi: 10.11999/JEIT150530

1.
2.
(Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China)

Funds:

The National 863 Program of China (2008AA121803), Funds of Key Laboratory of Airborne Optical Imaging and Measurement, Chinese Academy of Sciences (2012MS06)

Received Date: 2015-05-06
Rev Recd Date: 2015-12-02
Publish Date: 2016-03-19

Abstract

Abstract

The aerial camera takes photographs from sky. Conventional auto exposure algorithms can not be suitable for some special scenes such as the background is bright or dark and few strong interference points exist. Unsuitable exposure causes information losing in images. In order to solve this problem, an algorithm based on gray value is proposed. Firstly, it regulates the exposure preliminarily using the information of the histogram near 0 and 255. Then it obtains the regions of no interest in the image through the convolution of the histogram and weighted different proportion for the regions according to their area in the entire image. Finally, the weighted average is computed, which is regarded as the feedback controlling exposure. Experimental results indicate that image entropy of regions of interest increased more than 10% in dark or bright background. This method is suitable for many scenes, and meets the demands of the aerial camera.
- Image processing,
- Aerial camera,
- Histogram,
- Weighted average,
- Auto exposure

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References(30)

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