Infrared dim and small target detection based on total variation and multiple noise constraints modeling
Authors: 
Xiaowen Wang, Xiaoyan Xia, Qiao Li, Wei XueAuthors Info & Claims
Xiaowen Wang, Xiaoyan Xia, Qiao Li, Wei XueAuthors Info & ClaimsPages 1 - 5
Abstract
To improve the ability of infrared dim small target detection algorithm based on traditional infrared patch-image (IPI) model, a new detection model based on total variation and multiple noise constraints is proposed. We firstly transform the original infrared image into an IPI, and then the total variational regularization constrains the background patch-image in order to reduce the noise on the target image. In the meantime, the edge information of the image can be preserved to avoid excessive smoothness of the restored background image. Additionally, considering the lack of noise distribution in the patch-image, the combined and norm are introduced to describe the noise more accurately. The experimental results show that the proposed method can suppress the background clutter better and improve detection performance effectively.
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Published In
March 2022
121 pages
ISBN:9781450395823
DOI:10.1145/3529446
Copyright © 2022 ACM.
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Association for Computing Machinery
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Published: 15 July 2022
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IPMV 2022
IPMV 2022: 2022 4th International Conference on Image Processing and Machine Vision
March 25 - 27, 2022
Hong Kong, China
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