Infrared image segmentation method based on energy mapping relationship in gradient field

ZHANG Baohua; LIU He

doi:10.7510/jgjs.issn.1001-3806.2015.01.015

Image registration of infrared images have low contrast, complex background and serious noise interference. Over-segmentation or under-segmentation is prone to occur with traditional segmentation method. In order to solve the problems, an improved infrared image segmentation algorithm was proposed based on pulse coupled neural network (PCNN) and morphological methods. Firstly, texture sub-image was extracted according to energy distribution of the image and the texture sub-image was segmented by PCNN. The adaptive links strength of PCNN was set based on the changes of regional energy in gradient field. Because of the firing position of PCNN focused on infrared target portion, a clear coherent infrared target contour can be obtained from firing maps. Background interference was filtered out by morphological methods and high precision infrared target segmentation was achieved. The experimental results show that infrared image can be segmented accurately based on this method. By comparison, the segmentation result is better than traditional methods.

Infrared image segmentation method based on energy mapping relationship in gradient field

1. School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou 014010, China

Received Date: 2014-01-19

Accepted Date: 2014-02-17

Available Online: 2015-01-25

Abstract: Image registration of infrared images have low contrast, complex background and serious noise interference. Over-segmentation or under-segmentation is prone to occur with traditional segmentation method. In order to solve the problems, an improved infrared image segmentation algorithm was proposed based on pulse coupled neural network (PCNN) and morphological methods. Firstly, texture sub-image was extracted according to energy distribution of the image and the texture sub-image was segmented by PCNN. The adaptive links strength of PCNN was set based on the changes of regional energy in gradient field. Because of the firing position of PCNN focused on infrared target portion, a clear coherent infrared target contour can be obtained from firing maps. Background interference was filtered out by morphological methods and high precision infrared target segmentation was achieved. The experimental results show that infrared image can be segmented accurately based on this method. By comparison, the segmentation result is better than traditional methods.

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Reference (15)

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Infrared image segmentation method based on energy mapping relationship in gradient field

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