基于细节增强的红外微光图像融合技术研究

Research of Infrared and Low Light Image Fusion Based on Detail Enhancement

为了有效地对红外与微光图像进行融合,在获得良好的融合视觉效果并实现熵增的前提下,同时尽量减少算法复杂度,提出了一种基于细节增强的自适应权值融合方法,根据红外微光图像特点,进行自适应权值矩阵计算,并进行一次融合,再结合细节图进行二次融合。经过在MATLAB中采用三种常见算法和本算法对五类典型场景进行了仿真分析,结合主观和客观评价机制对比,本文的算法具有较好的标准差和熵增,主观融合效果也相对较优。最后,在嵌入式FPGA平台中进行了验证,实现了50 Hz图像的实时融合输出,在批量化生产中得到了应用。

In order to fuse infrared and low light image effectively,under the premise of obtaining good fusion visual effect and achieving entropy increase,while minimizing the complexity of the algorithm,an adaptive weight fusion method is proposed based on detail enhancement.According to the characteristics of infrared and low light image,the adaptive weight matrix is calculated,and the fusion is performed for the first time,and then combined with the detail image for the second fusion.After using three conventional algorithms and the algorithm of this paper to simulate and analyze five types of typical scenes in MATLAB,and combining with subjective and objective evaluation mechanism,the algorithm in this paper has a better standard deviation and entropy increase,and the subjective fusion effect is also relatively better.Finally,it is verified in the embedded FPGA platform to realize the real-time fusion output of 50 Hz images.