基于FPGA的短波红外图像灰度级拉伸算法实现

为了增强短波红外成像仪的成像对比度，提高目标的识别率，介绍了一种基于现场可编程门阵列(FPGA)的灰度拉伸算法的实现方法。利用视频数据两帧之间灰度分布近似的特性，通过统计上一帧图像的灰度分布，计算图像拉伸所需要的参数，处理当前帧的图像，达到实时处理的效果。在灰度统计模块中，利用FPGA的片上块随机存储器(Block RAM)资源，采用非倍频的流水线数字逻辑设计，避免了跨时钟域的操作，降低了系统状态机的复杂度，提高了系统的工作频率。采用国产320×256元InGaAs面阵探测器，搭载了Xilinx Artix-7系列芯片的实验平台进行实验，仿真结果表明,该方法能有效提高短波红外图像的对比度，具有占用资源少、运算速度快、成本低、可移植性高等优点，满足短波红外成像仪实时灰度拉伸处理的设计要求。

Implementation of grayscale stretching algorithm for short-wave infrared image based on FPGA

In order to enhance the contrast of short-wave infrared image and improve the recognition ratio of target, a method of grayscale stretching algorithm based on Field Programmable Gate Array(FPGA) is proposed in this paper. According to the similar grayscale distribution between two consecutive frames, the parameters needed for image stretching are obtained by calculating the grayscale distribution of the previous frame, so as to process current frame, and real-time processing is achieved. In the grayscale statistics module, the design of non-frequency-multiplied pipelined logic is applied using the Block RAM resources on the FPGA chip. The proposed method avoids clock domain crossing in the grayscale distribution calculation process, reduces the complexity of the state machine, and improves the maximum operating frequency of the system. A domestic 320×256 InGaAs detector and an experimental platform based on Xilinx Artix-7 series FPGA are utilized to carry out the experiment. The results show that this method can effectively improve the contrast of the short-wave infrared image, which has the advantages of less resource utilization, fast computing speed, low cost, high portability, etc. and meets the design requirements of the real-time grayscale stretching of the short-wave infrared camera.