- Tytuł:
- Infrared small-target detection under a complex background based on a local gradient contrast method
- Autorzy:
-
Yang, Linna
Xie, Tao
Liu, Mingxing
Zhang, Mingjiang
Qi, Shuaihui
Yang, Jungang - Powiązania:
- https://bibliotekanauki.pl/articles/2201024.pdf
- Data publikacji:
- 2023
- Wydawca:
- Uniwersytet Zielonogórski. Oficyna Wydawnicza
- Tematy:
-
small target detection
local gradient contrast
visual saliency
infrared image processing
kontrast lokalny
wyróżnienie wizualne
obrazowanie w podczerwieni - Opis:
- Small target detection under a complex background has always been a hot and difficult problem in the field of image processing. Due to the factors such as a complex background and a low signal-to-noise ratio, the existing methods cannot robustly detect targets submerged in strong clutter and noise. In this paper, a local gradient contrast method (LGCM) is proposed. Firstly, the optimal scale for each pixel is obtained by calculating a multiscale salient map. Then, a subblockbased local gradient measure is designed; it can suppress strong clutter interference and pixel-sized noise simultaneously. Thirdly, the subblock-based local gradient measure and the salient map are utilized to construct the LGCM. Finally, an adaptive threshold is employed to extract the final detection result. Experimental results on six datasets demonstrate that the proposed method can discard clutters and yield superior results compared with state-of-the-art methods.
- Źródło:
-
International Journal of Applied Mathematics and Computer Science; 2023, 33, 1; 33--43
1641-876X
2083-8492 - Pojawia się w:
- International Journal of Applied Mathematics and Computer Science
- Dostawca treści:
- Biblioteka Nauki
Artykuł