为了解决图像处理领域缺少一个描述目标信号显著程度的物理量的问题, 引用了光谱学中信背比的概念, 类比于信噪比的计算方法, 求出目标信号平均灰度值与背景平均灰度值之比, 直观地表示出目标信号与背景的对比度。同时, 为了解决视频中低速暗弱目标难以分辨与检测的问题, 提出了一种视频低速暗弱目标增强方法, 首先对视频首尾的连续多帧图像进行叠加差分运算, 得到平滑的差分图像, 然后进行灰度变换迭代, 获得高信背比的图像。实验结果表明, 信背比可以有效地描述了目标信号的显著程度, 采用提出的视频低速暗弱目标增强方法后, 目标信号的信噪比由1.84增加至9.18, 信背比由0.33增加至19.44, 提高了接近60倍, 暗弱目标的显著程度大幅度提高, 达到了视频低速暗弱目标增强的要求。

Previous studies have used signal-to-background ratio in spectroscopy to address the lack of physical quantities that describe target signal saliency in image processing. Similar to the signal-to-noise ratio calculation method, the ratio of the average gray value of the target signal to the average gray value of the background was obtained, therefore, the contrast between the target signal and the background was visually demonstrated . However, a video enhancement method was proposed for low-speed dim targets to distinguish and detect low-speed dim targets in videos. First, a smooth differential image was obtained by overlying the image sequences at the beginning and end of the video to distinguish between them. Then, an image with a high signal-to-background ratio was obtained by gray transformation iteration. Experimental results have shown that, the target signal saliency was effectively described by the signal-to-background ratio. Using the video enhancement method for low-speed dim targets, the signal-to-noise ratio of the target signal increased from 1.84 to 9.18, and the signal-to-background ratio increased from 0.33 to 19.44, which is approximately 60 times higher. The saliency of the low-speed dim target signal in the video has significantly improved, thus fulfilling the requirements for low-speed dim targets.