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Multi-source and Multi-feature Image Information Fusion Based on Compressive Sensing

Qingzhao Li, Fei Jiang
2016 TELKOMNIKA (Telecommunication Computing Electronics and Control)  
This paper uses the sparse representation method of compressive sensing theory, proposes a multi-source and multi-feature image information fusion method based on compressive sensing in accordance with  ...  the features of image fusion, performs sparsification processing on the source image with K-SVD algorithm and OMP algorithm to transfer from spatial domain to frequency domain and decomposes into low-frequency  ...  the measurement vector until the iterations reach the sparseness K [12] .  ... 
doi:10.12928/telkomnika.v14i2.2748 fatcat:v744jsl5bfg7vahamndvd3cbmy

A Geometric Dictionary Learning Based Approach for Fluorescence Spectroscopy Image Fusion

Zhiqin Zhu, Guanqiu Qi, Yi Chai, Penghua Li
2017 Applied Sciences  
In recent years, sparse representation approaches have been integrated into multi-focus image fusion methods.  ...  At last the sparse coefficients are fused by Max-L1 fusion rule and inverted to fused image. Due to the limitation of microscope, the fluorescence image cannot be fully focused.  ...  The proposed solution uses sparse feature to do image sparse representation and fusion.  ... 
doi:10.3390/app7020161 fatcat:3cf7f2vcmjcrveo4mjqsuh5cwq

An Integrated Dictionary-Learning Entropy-Based Medical Image Fusion Framework

Guanqiu Qi, Jinchuan Wang, Qiong Zhang, Fancheng Zeng, Zhiqin Zhu
2017 Future Internet  
Yang and Li [15] first applied the sparse-representation theory to an image fusion field. A joint sparse-representation image fusion method was proposed by Zhang and Fu [22] .  ...  Sparse-representation is widely applied to image denoising [10], image deblurring [11], image inpainting [12], super-resolution [13] , and image fusion [14, 15] .  ...  Image fusion techniques are used to combine multiple images from the same senor modality or different sensor modalities for enhancing visibility.  ... 
doi:10.3390/fi9040061 fatcat:lah7gfcoazhpfbfwygwwf2ntgi

Detecting Saliency in Infrared Images via Multiscale Local Sparse Representation and Local Contrast Measure

Xin Wang, Chunyan Zhang, Chen Ning, Yuzhen Zhang, Guofang Lv
2017 Mathematical Problems in Engineering  
To handle this problem, a novel saliency detection method based on multiscale local sparse representation and local contrast measure is proposed in this paper.  ...  First, a multiscale local sparse representation based approach is designed for detecting saliency in infrared images.  ...  algorithm based on multiscale local sparse representation and local contrast measure in this paper.  ... 
doi:10.1155/2017/2483169 fatcat:hcq4bupwrvc7pif5e3sk2zofca

High-quality indoor scene 3D reconstruction with RGB-D cameras: A brief review

Jianwei Li, Wei Gao, Yihong Wu, Yangdong Liu, Yanfei Shen
2022 Computational Visual Media  
In this paper, we make comparisons and analyses from the following aspects: (i) depth processing methods in 3D reconstruction are reviewed in terms of enhancement and completion, (ii) ICP-based, feature-based  ...  , and hybrid methods of camera pose estimation methods are reviewed, and (iii) surface reconstruction methods are reviewed in terms of surface fusion, optimization, and completion.  ...  For instance, DeepSDF [120] introduces a learned continuous SDF representation of a class of shapes that enables high-quality shape representation, interpolation, and completion from partial and noisy  ... 
doi:10.1007/s41095-021-0250-8 fatcat:z6ywcn4zujbptjaqrwkwhoyquu

A Novel Geometric Dictionary Construction Approach for Sparse Representation Based Image Fusion

Kunpeng Wang, Guanqiu Qi, Zhiqin Zhu, Yi Chai
2017 Entropy  
They applied the Discrete Cosine Transform(DCT) dictionary and orthogonal matching pursuit (OMP) method to sparse-representation based multi-focus image fusion.  ...  Sparse-representation based approaches have been integrated into image fusion methods in the past few years and show great performance in image fusion.  ...  This work was also supported by the Science and Technology Planning Project of Sichuan Province (Grant Nos. 2016JY0242, 2016GZ0210), and the Foundation of the Southwest University of Science and Technology  ... 
doi:10.3390/e19070306 fatcat:a465n4xzj5edlprzvjxf6vokii

Image Fusion Techniques-A Survey

Suvitha. N
2018 International Journal for Research in Applied Science and Engineering Technology  
The purpose of image fusion is to identify the focused regions from the source images and combine them to form a fused image.  ...  Image fusion is a process of combining two or more images captured from the same scene to produce a single image which contains the high-quality information from the source images.  ...  Features are extracted from the source image patches and sparse representation is computed over this learned dictionary model.  ... 
doi:10.22214/ijraset.2018.5048 fatcat:6lr7rwv7ebei5aob7uzjm4p5yy

Multi-Sensor Image Fusion: A Survey of the State of the Art

Bing Li, Yong Xian, Daqiao Zhang, Juan Su, Xiaoxiang Hu, Weilin Guo
2021 Journal of Computer and Communications  
An overview of existing fusion strategies is then introduced, after which the existing fusion quality measures are summarized.  ...  Based on the reported comparative results, recent image fusion and performance assessment algorithms were reviewed and categorized, after which a comprehensive evaluation of 40 fusion algorithms from recently  ...  Yu et al. used the first model (JSM-1) from the joint sparse representation method proposed in [65] to achieve image fusion [66] .  ... 
doi:10.4236/jcc.2021.96005 fatcat:ulm4hbfy5ndkdne6fng6ncyn3i

Pixel-level image fusion with simultaneous orthogonal matching pursuit

Bin Yang, Shutao Li
2012 Information Fusion  
Thus, this paper proposes a novel image fusion scheme using the signal sparse representation theory.  ...  Sparse representation is a new signal representation theory which explores the sparseness of natural signals.  ...  Acknowledgements The authors would like to thank the anonymous reviewers for their detailed review, valuable comments, and constructive suggestions.  ... 
doi:10.1016/j.inffus.2010.04.001 fatcat:66o35dgrqjfpfbdrn2efwira2y

PCNN-Based Image Fusion in Compressed Domain

Yang Chen, Zheng Qin
2015 Mathematical Problems in Engineering  
This paper addresses a novel method of image fusion problem for different application scenarios, employing compressive sensing (CS) as the image sparse representation method and pulse-coupled neural network  ...  Experimental results demonstrate that the proposed fusion method outperforms other fusion methods in compressed domain and is effective and adaptive in different image fusion applications.  ...  Acknowledgments This work is supported by National S&T Major Program (Grant no. 9140A1550212 JW01047) and by the "Twelfth Five" Preliminary Research Project of PLA (no. 402040202).  ... 
doi:10.1155/2015/536215 fatcat:oens4haxe5dehjpv6hyum2b25q

Multispectral and SAR Image Fusion Based on Laplacian Pyramid and Sparse Representation

Hai Zhang, Huanfeng Shen, Qiangqiang Yuan, Xiaobin Guan
2022 Remote Sensing  
Therefore, this paper presents a fusion framework to integrate the information from MS and SAR images based on the Laplacian pyramid (LP) and sparse representation (SR) theory.  ...  Both visual interpretation and statistical analyses demonstrate that the proposed method strikes a satisfactory balance between spectral information preservation and the enhancement of spatial and textual  ...  We are also grateful to the editor and the anonymous reviewers for their detailed review, valuable comments, and constructive suggestions.  ... 
doi:10.3390/rs14040870 fatcat:2lkukijvibdpzf75rmm5gwh7ia

LDA Feature Selection for Satellite Image Fusion in HAAR Wavelet

2016 International Journal of Science and Research (IJSR)  
Image fusion is a technique that integrate complimentary details from multiple input images such that the new image give more information and more suitable for the purpose of human visual perception.  ...  First discrete wavelet transform (DWT) for time to frequency conversion, feature extraction, feature selection based on LDA and finally classify the feature level fusion.  ...  This algorithm also overcomes the disadvantages of both PCA and Sparse representation.  ... 
doi:10.21275/v5i4.nov162737 fatcat:d3dklluhgzctrdxhw5pzwav34a

A Study on Image Retrieval Based on Tetrolet Transform

Devika Sarath, M Sucharitha
2018 International Journal of Engineering & Technology  
Image retrieval techniques vary with feature extraction methods and various distance measures.  ...  Retrieving images from the large databases has always been one challenging problem in the area of image retrieval while maintaining the higher accuracy and lower computational time.  ...  the sparsest covering from each partition is stored the non-redundancy in the wavelet basis result in sparse image representation.  ... 
doi:10.14419/ijet.v7i3.27.17964 fatcat:yd2iyf5rkbch5n22tzkr3dp4hy

Sparse patch-based representation with combined information of atlas for multi-atlas label fusion

Meng Yan, Hong Liu, Enmin Song, Yuejing Qian, Lianghai Jin, Chih-Cheng Hung
2018 IET Image Processing  
In this study, the authors propose a new sparse patch-based representation method using a local binary texture (LBT) in the atlas image and atlas label information for the multi-atlas label fusion.  ...  To obtain a higher accuracy in the multi-atlas patch-based label fusion method, it is essential to have the accurate similarity measure of selected patches.  ...  Acknowledgements We would like to thank Tongji Hospital affiliated with Huazhong University of Science and Technology, for giving their useful medical suggestions.  ... 
doi:10.1049/iet-ipr.2017.1108 fatcat:o3yp7sc7dzgrdbyeem3mentpnm

Fast face hallucination with sparse representation for video surveillance

Zhen Jia, Hongcheng Wang, Ziyou Xiong, Alan Finn
2011 The First Asian Conference on Pattern Recognition  
Our proposed algorithm uses sparse representation and the ANN method to enhance both global face shape and local high frequency information while greatly improving the processing speed, as confirmed empirically  ...  The eigenfaces are combined using the coefficients obtained from sparse representation and added into the interpolated low-resolution face.  ...  . • A sparse representation method is used to estimate the coefficients for eigen-face fusion.  ... 
doi:10.1109/acpr.2011.6166702 dblp:conf/acpr/JiaWXF11 fatcat:oxx4yfyfwjfhnkbbxitkudamr4
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