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Deep Gradual Multi-Exposure Fusion via Recurrent Convolutional Network

Je-Ho Ryu, Jong-Han Kim, Jong-Ok Kim
2021 IEEE Access  
The performance of multi-exposure image fusion (MEF) has been recently improved with deep learning techniques but there are still a couple of problems to be overcome.  ...  In this paper, we propose a novel MEF network based on recurrent neural network (RNN).  ...  Section II introduces related works on CNN-based multi-exposure image fusion. Section III describes our RNN-based multiexposure image fusion architecture.  ... 
doi:10.1109/access.2021.3122540 fatcat:xv5fy3br5jezxnf2naa7z7fjb4

Editorial: Recent advances in artificial neural networks and embedded systems for multi-source image fusion

Xin Jin, Jingyu Hou, Shin-Jye Lee, Dongming Zhou
2022 Frontiers in Neurorobotics  
Editorial on the Research Topic Recent advances in artificial neural networks and embedded systems for multi-source image fusion In the first work entitled "Multi-Focus Color Image Fusion Based on Quaternion  ...  Multi-Scale Singular Value Decomposition (QMSVD)", Wan et al. employed multichannel quaternion multi-scale singular value to decompose the multi-focus color images, and a set of low-frequency and high-frequency  ...  In the work entitled "Multi-Exposure Image Fusion Algorithm Based on Improved Weight Function", Xu et al. proposed a multi-exposure image fusion method based on the Laplacian pyramid.  ... 
doi:10.3389/fnbot.2022.962170 fatcat:gjrefhvxqzayrpalphnxrw7z2y

De-fencing and Multi-Focus Fusion using Markov Random Field and Image Inpainting

Hannan Adeel, M Mohsin Riaz, Syed Sohaib Ali
2022 IEEE Access  
Multi-focus image fusion aims at combining source information from differently focused images. Fusion of multi-focus images has great applications in machine vision.  ...  The paper focuses on removal of fence occlusions in multi-focus images. The proposed model extracts fence occlusion map using salient image features, and refined by morphological operators.  ...  The scheme learns overcomplete dictionary using patch based clustering to transfer structural information in all-in-focus images. Similarly, Tan et al.  ... 
doi:10.1109/access.2022.3148761 fatcat:5pw3mfe4yndppp5hmspi2exfle

Evaluation of Retinal Image Quality Assessment Networks in Different Color-spaces [article]

Huazhu Fu, Boyang Wang, Jianbing Shen, Shanshan Cui, Yanwu Xu, Jiang Liu, Ling Shao
2019 arXiv   pre-print
Existing RIQA methods focus on the RGB color-space and are developed based on small datasets with binary quality labels (i.e., 'Accept' and 'Reject').  ...  Then, we analyze the influences on RIQA of different color-spaces, and propose a simple yet efficient deep network, named Multiple Color-space Fusion Network (MCF-Net), which integrates the different color-space  ...  The original RGB image is first transferred to HSV and LAB color-spaces, and fed into the base networks. The base networks generate image features by employing multi-scale CNN layers.  ... 
arXiv:1907.05345v3 fatcat:mgef7xecobgnljke6p43pobxlm

Multi-focus Image Fusion using Fully Convolutional Two-stream Network for Visual Sensors

2018 KSII Transactions on Internet and Information Systems  
We propose a deep learning method for multi-focus image fusion.  ...  In Recent years, image fusion approaches are proposed using machine learning (ML) algorithms for the classification of focused image regions.  ...  (a) (b) (c) (d) (e) (f) (g) (h) (i) (j) (k) (l) As shown in Fusion on multi-focus color images In this section, fusion experiments on a pair of multi-focus color images blurred with different level  ... 
doi:10.3837/tiis.2018.05.019 fatcat:xmdfs3ft2vdxzjgi6coxqparde

MCRD‐Net: An unsupervised dense network with multi‐scale convolutional block attention for multi‐focus image fusion

Ding Zhou, Xin Jin, Qian Jiang, Li Cai, Shin‐jye Lee, Shaowen Yao
2022 IET Image Processing  
This paper proposes an unsupervised dense network for multi-focus image fusion.  ...  Multi-focus image fusion technology solves the problem of limited depth of field of the optical lens. It can extract different focus parts under the same target to synthesize a fullfocus image.  ...  (SR) [23] and so on, have been introduced in multi-focus image fusion.  ... 
doi:10.1049/ipr2.12430 fatcat:ebcfhaz5qrdk3f3gumtxgbxtsu

Deep Visible and Thermal Image Fusion for Enhanced Pedestrian Visibility

Ivana Shopovska, Ljubomir Jovanov, Wilfried Philips
2019 Sensors  
In this paper, we propose a learning-based method for visible and thermal image fusion that focuses on generating fused images with high visual similarity to regular truecolor (red-green-blue or RGB) images  ...  Compared to existing methods we can better learn context and define fusion rules that focus on the pedestrian appearance, while that is not guaranteed with methods that focus on low-level image quality  ...  Focusing on context-based image features in addition to low-level-based ones helps in optimizing the visualization of specific objects of interest.  ... 
doi:10.3390/s19173727 pmid:31466378 pmcid:PMC6749306 fatcat:ykjkwe7xhbh5pf3f54ez34soi4

Fast and Efficient Zero-Learning Image Fusion [article]

Fayez Lahoud, Sabine Süsstrunk
2019 arXiv   pre-print
Then, we validate its effectiveness and speed on thermal, medical, and multi-focus fusion. We also apply it to multiple image inputs such as multi-exposure sequences.  ...  We propose a real-time image fusion method using pre-trained neural networks. Our method generates a single image containing features from multiple sources.  ...  The third dataset consists of 20 commonly used images in multi-focus fusion ('Book', 'Clock', 'Desk', etc.) in addition to the multi-focus color images from the Lytro dataset [50] .  ... 
arXiv:1905.03590v1 fatcat:o75pg6dfgjckbd2hy57ciuhd5a

Rethinking the Image Fusion: A Fast Unified Image Fusion Network based on Proportional Maintenance of Gradient and Intensity

Hao Zhang, Han Xu, Yang Xiao, Xiaojie Guo, Jiayi Ma
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
infrared and visible image fusion, multi-exposure image fusion, medical image fusion, multi-focus image fusion and pan-sharpening.  ...  In this paper, we propose a fast unified image fusion network based on proportional maintenance of gradient and intensity (PMGI), which can end-to-end realize a variety of image fusion tasks, including  ...  (Paul, Sevcenco, and Agathoklis 2016) propose a general algorithm for multi-focus and multi-exposure image fusion, which is based on blending the gradients of the luminance components of source images  ... 
doi:10.1609/aaai.v34i07.6975 fatcat:pwela7q5trbyjc2qzvqnkyw35y

Multi-View Image Fusion

Marc Comino Trinidad, Ricardo Martin-Brualla, Florian Kainz, Janne Kontkanen
2019 2019 IEEE/CVF International Conference on Computer Vision (ICCV)  
Figure 1 : We present a method for multi-view image fusion that is a applicable to a variety of scenarios: a higher resolution monochrome image is colorized with a second color image (top row), two color  ...  Inputs Outputs Color EV+2 Color EV-1 HDR Fusion Color EV+2 Color EV-1 DSLR Low-def stereo Detail Transfer Stereo DSLR Color Transfer Mono Color High-def mono Color High-def color Denoised High-def stereo  ...  Conclusion We focused on the problem of multi-view image fusion, and introduced PixelFusionNet, a novel end-to-end learnable architecture.  ... 
doi:10.1109/iccv.2019.00420 dblp:conf/iccv/TrinidadMKK19 fatcat:5neiisdahrdmhk7oq7ulytfpia

Front Matter: Volume 11756

Lynne L. Grewe, Erik P. Blasch, Ivan Kadar
2021 Signal Processing, Sensor/Information Fusion, and Target Recognition XXX  
These two-number sets start with 00, 01, 02, 03, 04, 0M Risk-based security: from theory to practice INFORMATION FUSION METHODOLOGIES AND APPLICATIONS III 0N Anomaly detection of unstructured big data  ...  for dynamic search INFORMATION FUSION METHODOLOGIES AND APPLICATIONS IV 0R Anomaly detection with noisy and missing data using a deep learning architecture 11756 0S Fairness-by-design Dempster-Shafer  ...  Conclusions Deep Learning has the potential to focus the model development based on a corpus of multisource data.  ... 
doi:10.1117/12.2598593 fatcat:5afkuwltljctxayaup2rz2njly

Multi-Focus Image Fusion Based on Multi-Scale Generative Adversarial Network

Xiaole Ma, Zhihai Wang, Shaohai Hu, Shichao Kan
2022 Entropy  
In this paper, an end-to-end multi-focus image fusion method based on a multi-scale generative adversarial network (MsGAN) is proposed that makes full use of image features by a combination of multi-scale  ...  The methods based on the convolutional neural network have demonstrated its powerful information integration ability in image fusion.  ...  In addition, there are three kinds of image fusion at the pixel level: image fusion based on the spatial domain, image fusion based on the transform domain, and image fusion based on deep learning.  ... 
doi:10.3390/e24050582 pmid:35626467 pmcid:PMC9140435 fatcat:ectjlg5zejcq3o4w7nkf2itrau

Fusion PSPnet Image segmentation based method for multi-focus image fusion

Jingchun Zhou, Mingliang Hao, Dehuan Zhang, Peiyu Zou, Weishi Zhang
2019 IEEE Photonics Journal  
A novel image segmentation method for multi-focus image fusion is proposed.  ...  Finally, 20 couples of color multi-focus images are employed as experimental datasets, and the contrast results show that the proposed method has a better fusion visual effect than the other state-of-the-art  ...  Therefore, in order to improve these defects, and considering that multi-focus image fusion is a dichotomous problem actually, a multi-focus image fusion framework based on image segmentation using PSPnet  ... 
doi:10.1109/jphot.2019.2950949 fatcat:2ukalkya3rgvfc7ywpktlkeutu

Exploiting Superpixels for Multi-Focus Image Fusion

Areeba Ilyas, Muhammad Shahid Farid, Muhammad Hassan Khan, Marcin Grzegorzek
2021 Entropy  
Multi-focus image fusion is the process of combining focused regions of two or more images to obtain a single all-in-focus image.  ...  Qualitative and quantitative evaluations are performed to assess the performance of the proposed method on a benchmark multi-focus image fusion dataset.  ...  A number multi-focus image fusion techniques based on deep learning (DL) have been presented using convolutional neural networks (CNNs), such as in [52] [53] [54] [55] [56] .  ... 
doi:10.3390/e23020247 pmid:33670018 fatcat:ty5mdv5ftbgyvhlsgn4phb2mf4

The bilateral solver for quality estimation based multi-focus image fusion [article]

Jingwei Guan, Yibo Chen, Wai-kuen Cham
2019 arXiv   pre-print
In this work, a fast Bilateral Solver for Quality Estimation Based multi-focus Image Fusion method (BS-QEBIF) is proposed.  ...  Since the visual quality of an image patch is highly correlated with its focus level, the focus-level maps are preliminarily obtained based on visual quality scores, as pre-estimations.  ...  from the multi-focus source images to the fusion results based on the information theory.  ... 
arXiv:1904.01417v1 fatcat:2qudttwgond6vomxx4g5kijnou
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