为了解决红外实时图像处理系统中热像仪输出动态范围大和监视器显示输出动态范围小之间的矛盾，满足信息处理系统大数据量和高实时性的要求，设计了一种新的基于现场可编程门阵列(FPGA)实现的红外实时图像增强算法。首先采用均值滤波的思想统计图像的局部极值，然后使用多级均值法计算图像灰度变换区间分界点，最后对图像做分段线性灰度变换，整个算法通过FPGA实现。实验结果表明，该方法不仅解决了非制冷红外焦平面阵列探测器输出值随其工作时间变化的问题，而且消除了图像中探测器盲元的干扰，丰富了图像背景细节，增强了图像显示效果。与直方图变换等传统图像增强算法相比，该算法计算时间缩短了1.38 ms，占用存储资源减少了97.6%。在工程应用上，该方案简单可靠，成本较低，易于FPGA实现，可为其他红外实时图像处理系统的设计提供参考。

There is a contradiction between the 14 bits output data of an infrared thermal imager and the 8 bits input data of its monitor in a real-time infrared image processing system. A novel algorithm for real-time infrared image enhancement based on Field Programmble Gate Array(FPGA) is proposed not only to solve this problem but also to satisfy the real-time and mass data needs of the system. Firstly, an image mean filter is used to compute the local limit values for each frame dynamically. Secondly, a multi-level average statistics method is designed to calculate the values of segment points for each gray normalization partition. Finally, the mean of different linear normalizations on different gray level segments is calculated to enhance the infrared image. The whole algorithm is developed on FPGA hardware with Verilog language. Experimental results show that this algorithm resolves the problem that the output values of an un-cooled focal plane array detector vary with its working life. Moreover, the algorithm reduces the impact from bad pixels, and enhances the detail of an image that has objects at both high and low temperatures in a scene. Compared with histogram projection, one of the most traditional image enhancement methods, this algorithm shortens the computation time by about 1.38 ms and the memory resource reduces by 97.6%. It can be implemented more easily by FPGA and performed better in a real-time infrared image enhancement system. In terms of engineering applications, the proposed scheme with simple architecture, high reliability and low cost characters can provide a valuable reference for future designs of real-time infrared image processing systems.