Infrared ship image enhancement method based on gray interval segmentation

Tianhao Hwang; Shuhua Wang

doi:10.1117/12.2552234

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31 January 2020 Infrared ship image enhancement method based on gray interval segmentation

Tianhao Hwang, Shuhua Wang

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Proceedings Volume 11427, Second Target Recognition and Artificial Intelligence Summit Forum; 114272A (2020) https://doi.org/10.1117/12.2552234
Event: Second Target Recognition and Artificial Intelligence Summit Forum, 2019, Changchun, China

Abstract

The main features of ship targets in infrared scene are low contrast, low signal-to-noise ratio and little detail information. In view of these characteristics, an infrared image enhancement algorithm based on gray interval segmentation is proposed in this paper. This algorithm expounds the imaging principle of infrared ship image from the perspective of radiology. According to the gray distribution of the image, the original image is segmented into gray interval sub images by using the gray histogram of the infrared image, and then the details of each sub image are enhanced separately. Finally, the final details of each sub image are enhanced by weighted linear superposition. The results show that the edge brightness and contrast of the image are obviously improved by the proposed algorithm. Compared with the traditional gray level compression method and the global histogram equalization method, the over-saturation phenomenon is obviously improved, and it is easy to realize.

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Tianhao Hwang and Shuhua Wang "Infrared ship image enhancement method based on gray interval segmentation", Proc. SPIE 11427, Second Target Recognition and Artificial Intelligence Summit Forum, 114272A (31 January 2020); https://doi.org/10.1117/12.2552234

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