@misc{Chen_Yanling_Infrared_2023,
 author={Chen, Yanling and Cheng, Lianglun and Wu, Heng and Chen, Ziyang and Li, Feng},
 contributor={Urbańczyk, Wacław. Redakcja},
 identifier={DOI: 10.37190/oa230104},
 year={2023},
 rights={Wszystkie prawa zastrzeżone (Copyright)},
 publisher={Oficyna Wydawnicza Politechniki Wrocławskiej},
 description={Optica Applicata, Vol. 53, 2023, nr 1, s. 49-64},
 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={We propose a high-quality infrared and visible image fusion method based on a deep wavelet-dense network (WT-DenseNet). The WT-DenseNet includes three network layers, the hybrid feature extraction layer, fusion layer, and image reconstruction layer. The hybrid feature extraction layer is composed of a wavelet and dense network. The wavelet network decomposes the feature map of the visible and infrared images into low-frequency and high-frequency components, respectively. The dense network extracts the salient features. A fusion layer is designed to integrate low-frequency and salient features. Finally, the fusion images are outputted by an image reconstruction layer. The experimental results demonstrate that the proposed method can realize high-quality infrared and visible image fusions, and the performance of the proposed method is better than that of the six recently published fusion methods in terms of contrast and detail performance.},
 type={artykuł},
 title={Infrared and visible image fusion with deep wavelet-dense network},
 keywords={optyka, infrared image, image fusion, image processing, infrared image enhancement},
}