Journal ArticleDOI
Multi-focus image fusion with a deep convolutional neural network
TLDR
A new multi-focus image fusion method is primarily proposed, aiming to learn a direct mapping between source images and focus map, using a deep convolutional neural network trained by high-quality image patches and their blurred versions to encode the mapping.About:
This article is published in Information Fusion.The article was published on 2017-07-01. It has received 826 citations till now. The article focuses on the topics: Image fusion & Convolutional neural network.read more
Citations
More filters
Proceedings ArticleDOI
Multi-Focus Image Fusion Based on Improved CNN
TL;DR: The fusion method based on improved CNN model is proposed for multi-focus images and effectively avoids grayscale discontinuity, artifacts and other problems, and is better than classical methods the authors selected.
Journal ArticleDOI
HyperTDP-Net: A Hyper-densely Connected Compression-and-Decomposition Network Based on Trident Dilated Perception for PET and MRI Image Fusion
TL;DR: HyperTDP-Net as discussed by the authors proposes a novel end-to-end medical image fusion model for PET and MRI images to achieve information interaction between different pathways, termed as hyper-densely connected compression-and-decomposition network based on trident dilated perception.
Content aware multi-focus image fusion for high-magnification blood film microscopy
Etru,Anescu,Ichael,Haw,Ydia,Eary,Z. .,Ajiczek,Hristopher,Endkowski,Émy,Laveau,Una,Lmi,Iobele,B. J.,Rown,Elmiro,Ernández,R. -,Eyes +20 more
TL;DR: In this paper , a content-aware multi-focus image fusion approach based on deep learning was proposed to extend the depth-of-field of high magnification objectives effectively, using 2-fold fewer focal planes than normally required.
Journal ArticleDOI
Mcnn: Conditional Focus Probability Learning to Multi-Focus Images Via Mutually Coupled Neural Network
Journal ArticleDOI
Super-Resolution Reconstruction Model of Spatiotemporal Fusion Remote Sensing Image Based on Double Branch Texture Transformers and Feedback Mechanism
TL;DR: Wang et al. as mentioned in this paper proposed a spatiotemporal fusion model of remote sensing images based on a dual branch feedback mechanism and texture transformer, which merges the benefits of transformer and convolution network.
References
More filters
Proceedings Article
ImageNet Classification with Deep Convolutional Neural Networks
TL;DR: The state-of-the-art performance of CNNs was achieved by Deep Convolutional Neural Networks (DCNNs) as discussed by the authors, which consists of five convolutional layers, some of which are followed by max-pooling layers, and three fully-connected layers with a final 1000-way softmax.
Journal ArticleDOI
Gradient-based learning applied to document recognition
Yann LeCun,Léon Bottou,Léon Bottou,Yoshua Bengio,Yoshua Bengio,Yoshua Bengio,Patrick Haffner +6 more
TL;DR: In this article, a graph transformer network (GTN) is proposed for handwritten character recognition, which can be used to synthesize a complex decision surface that can classify high-dimensional patterns, such as handwritten characters.
Journal ArticleDOI
Image quality assessment: from error visibility to structural similarity
TL;DR: In this article, a structural similarity index is proposed for image quality assessment based on the degradation of structural information, which can be applied to both subjective ratings and objective methods on a database of images compressed with JPEG and JPEG2000.
Proceedings ArticleDOI
Fully convolutional networks for semantic segmentation
TL;DR: The key insight is to build “fully convolutional” networks that take input of arbitrary size and produce correspondingly-sized output with efficient inference and learning.
Proceedings Article
Rectified Linear Units Improve Restricted Boltzmann Machines
Vinod Nair,Geoffrey E. Hinton +1 more
TL;DR: Restricted Boltzmann machines were developed using binary stochastic hidden units that learn features that are better for object recognition on the NORB dataset and face verification on the Labeled Faces in the Wild dataset.
Related Papers (5)
A general framework for image fusion based on multi-scale transform and sparse representation
Yu Liu,Shuping Liu,Zengfu Wang +2 more