## 2 High Dynamic Infrared Image Enhancement Algorithm  
Thanks to the development of infrared detection technology, most of the current infrared detectors use 14 bit or 16 bit digital-to-analogue conversion technology, with higher precision quantitative sampling, so that the high dynamic infrared image can contain richer scene detail information. However, the traditional display has only 256 grey levels. After the image is compressed and displayed, the detail information will be merged due to the small difference and cannot be displayed, resulting in a waste of data resources; therefore, it is necessary to adopt reasonable and effective detail contrast enhancement and compression techniques.  
In 2005, FLIR Corporation released digital detail enhancement (DDE) technology, which is defined in the digital detail enhancement (DDE) technical note as follows: FLIR Systems has developed a powerful algorithm to help users solve the problem of locating low-contrast targets in high-dynamic-range scenes. DDE is an advanced, nonlinear image-processing algorithm that preserves high dynamic range detail in an image and enhances the image detail to match the total dynamic range of the original image background [18]. The essence is that the high dynamic two-dimensional image is processed by layering and decomposed into a low-frequency information layer and a high-frequency information layer.  
The low-frequency information layer contains a large amount of background information, which needs to be processed to improve the contrast. The high-frequency information layer contains the contour of the image, edge information, and noise information, which needs to be processed by the noise-reduction process to improve the details of the image. Finally, the compression process is carried out, which can better retain the detailed information of the image [18]. Since then, the processing mode based on the idea of layering has gradually been used in infrared image processing and achieved good results. [PERSON] and others proposed a dynamic range enhancement algorithm based on bilateral filtering [19], which retains the high-frequency detail information of the image when it enhances the details of high dynamic range infrared images. However, this method can easily produce the phenomenon of edge-flip in the region of large grey-scale changes, which leads to the appearance of halo artifacts in the processed infrared images. [PERSON] and others proposed an infrared image detail enhancement algorithm based on guided filtering [20]. The algorithm uses a guided filter instead of a bilateral filter as a frequency divider tool. [PERSON] and others weighted the details of the guided filtering based on this; the weights were used to stratify the image, and good experimental results were achieved [21]. However, image layering based on guided filtering requires manual threshold setting and high computational complexity, resulting in the poor scene applicability of the algorithm as well as real-time processing. Through the research and study of DDE technology and the comparison and analysis of a variety of algorithms, the algorithm in this study is proposed, and its algorithm flow is shown in Figure 1.  
This research will provide an effective method for high dynamic infrared image processing. This study's algorithm can effectively improve the quality of high dynamic infrared images, enhance the image details, and improve the accuracy of target detection and tracking, so as to provide a more reliable solution for applications in military, security, medical and industrial fields.