Refined Multi-Focus image fusion using Multi-Scale neural network with SpSwin Autoencoder-based matting

This paper proposes a novel method based on a Multi-Scale neural network with a SpatialSwin (SpSwin) Autoencoder-based matting for the multi-focus image fusion (MFIF) task. The proposed strategy introduces several innovations to enhance image quality and address challenges like boundary precision an...

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Veröffentlicht in:	Expert systems with applications Jg. 276; S. 126980
Hauptverfasser:	Jiang, Shengchuan, Yu, Shanchuan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.06.2025
Schlagworte:	And Hierarchical Feature Enhancement Block (HFEB) Combined Convolutional Blocks (CCBs) Depthwise Separable Convolution (DSC) Image fusion Pyramid Squeeze Attention (PSA) SpatialSwin (SpSwin) Autoencoder Transpose Convolution (TC) Combined Convolutional Blocks (CCBs) Pyramid Squeeze Attention (PSA) And Hierarchical Feature Enhancement Block (HFEB) Depthwise Separable Convolution (DSC) SpatialSwin (SpSwin) Autoencoder Transpose Convolution (TC) Image fusion
ISSN:	0957-4174
Online-Zugang:	Volltext
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