Infrared weak small target detection is one of the key technologies in the infrared early warning system, infrared imaging guidance system and wide-field view surveillance system etc. In the complex and low signal-to-noise ratio background environment, the target has only a few pixels. There is no shape and texture information to use. All of the above issues bring great difficulties to infrared dim-small target detection. In this paper, in order to deal with the shortcoming of large pixel tracking in moving target detection algorithm based on time domain filtering, apply the dim target detection based on Laplace operator to the subject of this paper, the false alarm points obviously to be less, and the target point is usually in the form of a single pixel, lay a good foundation for reducing the complexity of the algorithm.

Background suppression of weak small targets in infrared image is the key of image tracking and monitoring, especially under the cloud background. In the area of image signal processing, there are a lot of background suppression methods can be used to image filter by combining the characteristics of infrared image under the cloud background. In this paper, we introduce three typical background filter methods such as pulse median filter, multi-structural morphological filter and wavelet threshold method, realize them using MATLAB, and analyze their performances of background suppression of weak small targets in infrared image under the cloud background.

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