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Under-exposed image enhancement using exposure compensation

机译：使用曝光补偿的曝光不足图像增强

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Exposure is critical in the imaging process, since if the lighting condition is poor, the quality and visibility of images will be severely degraded. In this paper, we propose a fully automatic image enhancement algorithm that can efficiently solve the under-exposed problem. The basic idea behind this method comes from the common technique of photography: the exposure compensation. For poorly exposed images like nighttime images and backlit images, we first examine the level of exposure by adapting the Zone system used in photography, and then use exposure compensation to correct the insufficient lightness. Our experiments demonstrate compared to existing methods, the proposed algorithm not only presents more nature color and visible details, but also leads to less unpleasing artifacts. It is particularly useful for image quality enhancement for a video recorded by event data recorder (EDR) or by a video-based driving assistance system in a vehicle.
机译：曝光在成像过程中至关重要，因为如果光照条件较差，则图像的质量和可见度将严重下降。在本文中，我们提出了一种可以有效解决曝光不足问题的全自动图像增强算法。该方法背后的基本思想来自摄影的通用技术：曝光补偿。对于夜间和背光图像等曝光差的图像，我们首先通过调整摄影中使用的区域系统来检查曝光水平，然后使用曝光补偿来校正亮度不足。我们的实验表明，与现有方法相比，该算法不仅呈现出更多的自然色和可见细节，而且减少了不愉快的伪像。这对于提高由事件数据记录器（EDR）或车辆中基于视频的驾驶辅助系统记录的视频的图像质量特别有用。

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