压缩感知理论在红外成像中的应用

A New Infrared Imaging Method Based on Random Compressive Sensing

分析了红外图像的数据特性，并对红外数据进行稀疏化处理，提出了基于压缩感知理论的红外图像成像方法。在红外图像测量平面使用随机观测矩阵进行观测，以少量的数据采样信息获得重建红外图像的足够信息。由实验和仿真计算可知，压缩感知理论应用于红外成像技术，降低了数据采样量，提高了采样速度，并能以较小的误差实现红外图像的重构。

Considering the sparse structure of actual infrared image, a new infrared imaging method based on random compressive sensing is proposed in this paper. Using a small quantity of gathered data, this method can reconstruct subtotal information of infrared image. According to the conclusion from emulation mode, the infrared imaging method based on random compressive sensing is more efficacious than traditional method, reconstructs the original infrared image effectively.