- Home
- Publications
- Publication Search
- Publication Details
Title
Structural Similarity Loss for Learning to Fuse Multi-Focus Images
Authors
Keywords
-
Journal
SENSORS
Volume 20, Issue 22, Pages 6647
Publisher
MDPI AG
Online
2020-11-20
DOI
10.3390/s20226647
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- MFF-GAN: An unsupervised generative adversarial network with adaptive and gradient joint constraints for multi-focus image fusion
- (2020) Hao Zhang et al. Information Fusion
- U2Fusion: A Unified Unsupervised Image Fusion Network
- (2020) Han Xu et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Multilevel Features Convolutional Neural Network for Multifocus Image Fusion
- (2019) Yong Yang et al. IEEE Transactions on Computational Imaging
- Multi-Focus Image Fusion Using U-Shaped Networks With a Hybrid Objective
- (2019) Huaguang Li et al. IEEE SENSORS JOURNAL
- Robust Multi-Focus Image Fusion Using Edge Model and Multi-Matting
- (2018) Yibo Chen et al. IEEE TRANSACTIONS ON IMAGE PROCESSING
- Pixel convolutional neural network for multi-focus image fusion
- (2018) Han Tang et al. INFORMATION SCIENCES
- Pixel-wise regression using U-Net and its application on pansharpening
- (2018) Wei Yao et al. NEUROCOMPUTING
- Fast and Accurate Image Super-Resolution with Deep Laplacian Pyramid Networks
- (2018) Wei-Sheng Lai et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Multi-focus image fusion using Content Adaptive Blurring
- (2018) Muhammad Shahid Farid et al. Information Fusion
- Pixel-level image fusion: A survey of the state of the art
- (2017) Shutao Li et al. Information Fusion
- Boundary finding based multi-focus image fusion through multi-scale morphological focus-measure
- (2017) Yu Zhang et al. Information Fusion
- Multi-focus image fusion with a deep convolutional neural network
- (2017) Yu Liu et al. Information Fusion
- Image Super-Resolution Using Deep Convolutional Networks
- (2016) Chao Dong et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Steerable local frequency based multispectral multifocus image fusion
- (2015) Vijay N. Gangapure et al. Information Fusion
- Multi-focus image fusion using dictionary-based sparse representation
- (2015) Mansour Nejati et al. Information Fusion
- Multi-focus image fusion with dense SIFT
- (2015) Yu Liu et al. Information Fusion
- Adaptive fusion method of visible light and infrared images based on non-subsampled shearlet transform and fast non-negative matrix factorization
- (2014) Weiwei Kong et al. INFRARED PHYSICS & TECHNOLOGY
- Mutual spectral residual approach for multifocus image fusion
- (2013) Ashirbani Saha et al. DIGITAL SIGNAL PROCESSING
- Image Fusion With Guided Filtering
- (2013) Shutao Li et al. IEEE TRANSACTIONS ON IMAGE PROCESSING
- Discrete Cosine Transform based fusion of multi-focus images for visual sensor networks
- (2013) Y. Asnath Victy Phamila et al. SIGNAL PROCESSING
- Multifocus color image fusion based on quaternion curvelet transform
- (2012) Liqiang Guo et al. OPTICS EXPRESS
- Objective Assessment of Multiresolution Image Fusion Algorithms for Context Enhancement in Night Vision: A Comparative Study
- (2011) Z. Liu et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- A new image fusion performance metric based on visual information fidelity
- (2011) Yu Han et al. Information Fusion
- Image matting for fusion of multi-focus images in dynamic scenes
- (2011) Shutao Li et al. Information Fusion
- A novel algorithm of image fusion using shearlets
- (2010) Qi-guang Miao et al. OPTICS COMMUNICATIONS
- Multifocus image fusion using the nonsubsampled contourlet transform
- (2009) Qiang Zhang et al. SIGNAL PROCESSING
- Multifocus image fusion by combining curvelet and wavelet transform
- (2008) Shutao Li et al. PATTERN RECOGNITION LETTERS
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started