Recent advances via convolutional sparse representation model for pixel-level image fusion

Image fusion aims to integrate complementary information from different source images into the final output image. This plays a significant role in high-level vision tasks. However, image fusion methods based on sparse representation (SR) or conventional multiscale transform (MST) have some drawback...

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Vydané v:	Multimedia tools and applications Ročník 83; číslo 17; s. 52899 - 52930
Hlavní autori:	Pan, Yue, Lan, Tianye, Xu, Chongyang, Zhang, Chengfang, Feng, Ziliang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.05.2024 Springer Nature B.V
Predmet:	Algorithms Computer Communication Networks Computer Science Computer vision Data Structures and Information Theory Decomposition Deep learning Dictionaries Infrared imagery Medical imaging Medical research Multimedia Multimedia Information Systems Performance evaluation Pixels Representations Special Purpose and Application-Based Systems Track 6: Computer Vision for Multimedia Applications Trends Wavelet transforms Online convolutional sparse coding Convolutional sparse representation Online convolutional dictionary learning Convolutional dictionary learning Image fusion
ISSN:	1573-7721, 1380-7501, 1573-7721
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