光学
夜视
红外线的
背景(考古学)
可见光谱
计算机科学
计算机视觉
人工智能
物理
生物
古生物学
作者
Jin Zhu,Weiqi Jin,Li Li,Zhenghao Han,Xia Wang Xia Wang
标识
DOI:10.3788/col201816.013501
摘要
For better night-vision applications using the low-light-level visible and infrared imaging, a fusion framework for night-vision context enhancement (FNCE) method is proposed. An adaptive brightness stretching method is first proposed for enhancing the visible image. Then, a hybrid multi-scale decomposition with edge-preserving filtering is proposed to decompose the source images. Finally, the fused result is obtained via a combination of the decomposed images in three different rules. Experimental results demonstrate that the FNCE method has better performance on the details (edges), the contrast, the sharpness, and the human visual perception. Therefore, better results for the night-vision context enhancement can be achieved.
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