Mr. Chunming He Profile

Chunming He

at Nanjing Univ of Posts and Telecommunications

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Proceedings Article | 12 October 2020 Paper

Small infrared target detection via iteratively reweighted nuclear norm

Haoran Gao, Jinlei Ren, Chunming He , Lizhen Deng

Proceedings Volume 11574, 115740I (2020) https://doi.org/10.1117/12.2575815

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The process of infrared images via computer-based algorithms for better application is a frontier field integrating physical technology with computer science. One of the key techniques in infrared image processing is the detection of infrared targets. This technique is extensively applied in security and defense systems and search and tracking systems. However, due to their small size, dim light and lack of texture, the detection of infrared targets is a technical problem. One strategy to address this problem is to transform the detection work into a non-convex optimization problem of recovering a low-rank matrix (background) and a sparse matrix (target) from a patch-image matrix (original image) based on IPI (infrared patch-image) model. When targets are clear and recognizable, the APG (accelerated proximal gradient) algorithm works effectively to solve it. However, when targets become much dimmer and are screened by the intricate texture of background, the experimental detection results degrade dramatically. In order to solve this problem, a novel method via IRNN (iteratively reweighted nuclear norm) is proposed in this paper. Experimental results show that under different complicated backgrounds, targets with higher SCRG (signal-to-clutter ratio gain) values and BSF (background suppression factor) values can be acquired through IRNN algorithm compared with the APG algorithm, which means that our method performs better.

Proceedings Article | 12 October 2020 Paper

Vessel detection based on dual-operator log-pol top-hat filter

Lei Xu, Ze Wang, Chunming He, Guosheng Lu, Lizhen Deng

Proceedings Volume 11574, 115740H (2020) https://doi.org/10.1117/12.2575684

KEYWORDS: Clouds, Target detection, Lithium, 3D image processing, Image processing, Surveillance, Telecommunications, Image filtering, Structural design

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Vessel detection has been widely used in Marine Surveillance to automatically detect potential threats over a huge oceanic area. However, the uncertainty of ship direction and the interference of environment factors, such as sea waves and cloud, will greatly reduce the detection accuracy. In order to solve the above problems and provide robustness to environmental conditions, we combine the property of polar-logarithmic coordinate and proposed our method named “Dual-operator log-pol top-hat filter (DOLPTH)” to make better use of the difference information between the vessel and the background. Different situations are designed to test the performance of our algorithm compared with other algorithms. The experimental results show that in both cases, DOLPTH can maintain high accuracy and has good detection performance.

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