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The hyperspectral images of airplanes and flying birds are obtained by a xiSpec snapshot mosaic hyperspectral cameras, supported by the Interuniversity Microelectronics Centre (IMEC). The single frame Infrared Patch-Image (IPI) model is used to detect the small targets of airplanes and flying birds under complex cloud background in the hyperspectral images. Based on the non-local autocorrelation property of the background image, the method assumes that the target image is a sparse matrix and the background image is a low-rank matrix. The small target detection is transformed into an optimization problem of recovering the low-rank and sparse matrix. Using stable principal component tracking solution, the decomposed background and target are obtained. The results show that this method can detect bright and dark small targets in complex background at the same time, and the hyperspectral image can effectively improve the detection rate. More importantly, the detection ability is closely related to the intensity difference of the target against the background. Thus, the optimal waveband of different targets can be given by combining the target detection results and the intensity difference curves. This has a guiding significance for the design of specific point target detection payloads.
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