Low-Speed Small Target Detection Based on SVD and Superposition

Abstract

Abstract:

Abstract： In the case of the measurement noises obtained from the same pixel position in a set of images which are ergodic, the feasibility of superposition method for target detection was analyzed, based on which, a superposition-based lowspeed small target detection algorithm was proposed. First, the energy variation of the target synthesis images and the noise synthesis images were analysized, when the targets were non-overlapped, completely overlapped and partially overlapped. The analysis shows that with the increase in the superimposed number, the energy of the noise synthesis images is attenuated faster than that of the target synthesis images, thus ensuring an increase in the ratio of target to noise in synthesis images. Second, depending on the characteristics of singular values of the synthesis images, the uneven variations of the standardized singular values were used for target detection. The simulation verifies the attenuation of the target energy and noise energy of the synthesis images, and analyzes the impact of superimposed number， target size and strength on target detectability.

Key words: singular value decomposition (SVD), superposition, object detection

CLC Number:

TP 391

GAO Jingli1，WEN Chenglin2，LIU Meiqin1. Low-Speed Small Target Detection Based on SVD and Superposition[J]. Journal of Shanghai Jiaotong University, 2015, 49(06): 876-883.

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