@misc{Wang_Zhonghua_Aerial_2024,
 author={Wang, Zhonghua and He, Bangsheng and He, Wenjie},
 contributor={Urbańczyk, Wacław. Redakcja},
 identifier={DOI: 10.37190/oa240307},
 year={2024},
 rights={Wszystkie prawa zastrzeżone (Copyright)},
 publisher={Oficyna Wydawnicza Politechniki Wrocławskiej},
 description={Optica Applicata, Vol. 54, 2024, nr 3, s. 365-381},
 description={Optica Applicata is an international journal, published in a non-periodical form in the years 1971-1973 and quarterly since 1973. From the beginning of the year 2008, Optica Applicata is an Open Access journal available online via the Internet, with free access to the full text of articles serving the best interests of the scientific community. The journal is abstracted and indexed in: Chemical Abstracts, Compendex, Current Contents, Inspec, Referativnyj Zhurnal, SCI Expanded, Scopus, Ulrich’s Periodicals Directory},
 description={http://opticaapplicata.pwr.edu.pl/},
 language={eng},
 abstract={To solve the problem of false alarm rate in detecting infrared small targets under complex cloud backgrounds, a novel algorithm combining structure tensor and local contrast is proposed. The structure tensor can better describe the gradient distributions in the local image area, and its eigenvalues can also depict the characteristics of the area. Combining the weighted local contrast with eigenvalues, the small targets can be enhanced and the background can be suppressed. In addition, to highlight the target, the regional complexity is further used for weighting local contrast. The presented algorithm steps are as follows: firstly, Gaussian filtering is performed on the original image; secondly, the larger eigenvalue of the structure tensor matrix is used to calculate the local contrast through the difference operation; thirdly, the regional complexity is calculated by the gray difference between the central and surrounding regions for weighting the local contrast to generate a saliency map; finally, an adaptive threshold segmentation is performed on the saliency map to extract the real target. The comparative experiments show that the proposed algorithm can achieve the highest detection rate, lowest false alarm rate, and shortest running time.},
 type={artykuł},
 title={Aerial infrared small target detection algorithm combined structure tensor and local contrast},
 keywords={optyka, structure tensor, small target, regional complexity, local contrast, adaptive threshold segmentation},
}