Dim moving object detection based on projection into the 2D frequency domain

Di Xiaoguang; Lin Zhe; Chen Songlin

For the dim optical object difficult to fast and accurate detection, a novel algorithm based on the row and column maximum projection of image sequences into the 2D frequency domain was proposed. Firstly, in order to reduce the computation complexity and separate the moving object from the background, through projecting into the 2D frequency domain and removing the zero frequency components, the input video with global background motion compensation was transformed into image sequences comprising of dim small moving object and noise. Secondly, after the row and column maximum projection, the higher signal-to-noise ratio image sequences with dim moving target was obtained. Thirdly, through the principal motion filtering and image reconstruction, the dim moving object was detected. Finally, the proposed algorithm was applied to the dim moving object detection in the strong background noise. The simulation experiment results show the proposed algorithm can not only effectively detect the dim moving object but also have good signal-to-noise ratio of detection.

1. Control and Simulation Center,Harbin Institute of Technology,Harbin 150080,China;

2. Beijing Institute of Space Mechanics & Electricity,Beijing 100190,China

Received Date: 2013-04-13

Rev Recd Date: 2013-05-19

Publish Date: 2013-12-25

Key words:

dim moving object detection /
projection into the 2D frequency domain /
imaging guidance

Abstract: For the dim optical object difficult to fast and accurate detection, a novel algorithm based on the row and column maximum projection of image sequences into the 2D frequency domain was proposed. Firstly, in order to reduce the computation complexity and separate the moving object from the background, through projecting into the 2D frequency domain and removing the zero frequency components, the input video with global background motion compensation was transformed into image sequences comprising of dim small moving object and noise. Secondly, after the row and column maximum projection, the higher signal-to-noise ratio image sequences with dim moving target was obtained. Thirdly, through the principal motion filtering and image reconstruction, the dim moving object was detected. Finally, the proposed algorithm was applied to the dim moving object detection in the strong background noise. The simulation experiment results show the proposed algorithm can not only effectively detect the dim moving object but also have good signal-to-noise ratio of detection.

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Reference (21)

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Dim moving object detection based on projection into the 2D frequency domain

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