Zhendong Luo
Zhendong Luo has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Chang Ding
China Univ Min & Technol, Sch Informat & Control Engn, Xuzhou 221116, Peoples R China
2 shared publications - Siyang Chen
Xian Univ Sci & Technol, Coll Commun & Informat Technol, Xian 710699, Peoples R China
2 shared publications - Hai Liu
China University of Mining and Technology
1 shared publication J. Zhang
Guilin Univ Elect Technol, Sch Mech & Elect Engn, Guilin 541004, Peoples R China
1 shared publication- Weidong Zhang
Hainan University
1 shared publication - Yifeng Hou
School of Electronics and Information, Wuzhou University, Wuzhou 543002, China
1 shared publication
Latest Publications
- 1 December 2024
- Published by Brno University of Technology in Radioengineering
- Vol. 33 (4) , 721-732
Infrared Small Target Detection, High-Precision Localization and Segmentation: Using TDU Kernel
- 1 December 2024
- Published by Brno University of Technology in Radioengineering
- Vol. 33 (4) , 721-732
Infrared Small Target Detection, High-Precision Localization and Segmentation: Using TDU Kernel
- Open Access
- 20 July 2023
- Published by MDPI AG in Remote Sensing
- Vol. 15 (14) , 3623
An Effective Method of Infrared Maritime Target Enhancement and Detection with Multiple Maritime Scene
Aiming at maritime infrared target detection with low contrast influenced by maritime clutter and illumination, this paper proposes a Modified Histogram Equalization with Edge Fusion (MHEEF) pre-processing algorithm in backlight maritime scenes and establishes Local-Contrast Saliency Models with Double Scale and Modes (LCMDSM) for detecting a target with the properties of positive and negative contrast. We propose a local-contrast saliency mathematical model with double modes in the extension of only one mode. Then, the big scale and small scale are combined into one Target Detection Unit (TDU), which can approach the “from bottom to up” mechanism of the Visual Attention Model (VAM) better and identify the target with a suitable size, approaching the target’s actual shape. In the experimental results and analysis, clutter, foggy, backlight, and dim maritime scenes are chosen to verify the effectiveness of the target detection algorithm. From the enhancement result, the LCMDSM algorithm can achieve a Detection Rate (DR) with a value of 98.26% under each maritime scene on the average level and can be used in real-time detection with low computational cost.
- 20 July 2023
- Published by MDPI AG in Remote Sensing
- Vol. 15 (14) , 3623
Open AccessAn Effective Method of Infrared Maritime Target Enhancement and Detection with Multiple Maritime Scene
Aiming at maritime infrared target detection with low contrast influenced by maritime clutter and illumination, this paper proposes a Modified Histogram Equalization with Edge Fusion (MHEEF) pre-processing algorithm in backlight maritime scenes and establishes Local-Contrast Saliency Models with Double Scale and Modes (LCMDSM) for detecting a target with the properties of positive and negative contrast. We propose a local-contrast saliency mathematical model with double modes in the extension of only one mode. Then, the big scale and small scale are combined into one Target Detection Unit (TDU), which can approach the “from bottom to up” mechanism of the Visual Attention Model (VAM) better and identify the target with a suitable size, approaching the target’s actual shape. In the experimental results and analysis, clutter, foggy, backlight, and dim maritime scenes are chosen to verify the effectiveness of the target detection algorithm. From the enhancement result, the LCMDSM algorithm can achieve a Detection Rate (DR) with a value of 98.26% under each maritime scene on the average level and can be used in real-time detection with low computational cost.