红外热像是目前被广泛应用于各个领域的一种无损检测技术，但因设备的不足和使用环境的影响，红外图像会出现低分辨率、低对比度、低信噪比等缺陷，这无疑会对缺陷的定性和定量识别带来很大的困难，所以红外图像的处理则成为了无损检测中极其重要的环节，对整个工业领域的发展起着促进作用。本文介绍了红外技术中图像处理部分，包括预处理和图像识别；列举了目前在图像预处理阶段被广泛使用的处理技术，如神经网络、视网膜皮层、数字细节增强、Contourlet变换等技术，并简要列出其优缺点；介绍了主要运用于复合材料检测中的图像识别技术，如：温度信号重构、脉冲相位法、主成分分析、独立成分分析、区域生长法等技术，并给出了学者们的部分实验结果和实验结论；最后总结了该技术的发展趋势。

Infrared thermography is a nondestructive testing technology widely used across various fields. However, infrared images can have limitations, such as low resolution, low contrast, and low signal-to-noise ratios, when they are subjected to equipment defects or are influenced by the operating environment. These shortcomings lead to considerable difficulties in the qualitative and quantitative identification of defects; therefore, infrared image processing, which is a critical link in nondestructive testing, has the ability to promote the development of many industrial fields. This work focuses on the role of image processing in infrared technology, including preprocessing and image recognition, and enumerates processing techniques such as the neural networks, retina cortex, digital detail enhancement, and Contourlet transform, which are widely used in the image preprocessing stage. Advantages and disadvantages of these techniques are briefly listed. This work also introduces image recognition techniques principally used in composite material detection like temperature signal reconstruction, the pulse phase method, principal component analysis, independent component analysis, and the region growing method, and it provides some experimental results and conclusions from scholars. Finally, the development of this trend in infrared technology is summarized.