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Pixel-level image fusion with simultaneous orthogonal matching pursuit

Bin Yang, Shutao Li
2012 Information Fusion  
In addition, the simultaneous orthogonal matching pursuit technique is introduced to guarantee that different source images are sparsely decomposed into the same subset of dictionary bases, which is the  ...  Pixel-level image fusion integrates the information from multiple images of one scene to get an informative image which is more suitable for human visual perception or further image-processing.  ...  So, the simultaneous orthogonal matching pursuit (SOMP) [33] is used to resolve this problem.  ... 
doi:10.1016/j.inffus.2010.04.001 fatcat:66o35dgrqjfpfbdrn2efwira2y

Fusion Imaging in Pixel Level Image Processing Technique – A Literature Review

K Elaiyaraja, M Senthil Kumar
2018 International Journal of Engineering & Technology  
Pixel-level image fusion shows a vital role in medical imaging. In this paper, pixel-level image fusionsmethods are survived and review the fusion quality measures are being used.  ...  Finally this surveycomplete with different kinds of image fusion methods proposed and still there are so many imminent ways in image fusion applications.  ...  Orthogonal Matching Pursuit (OMP) algorithm, Gradient sparsity constraint which reflect the sharp edges[13], Simultaneous Orthogonal Matching Pursuit (SOMP) [13]and joint sparsity model are some of the  ... 
doi:10.14419/ijet.v7i3.12.15913 fatcat:3yrjf663zren3kvxktjuhqtxjq

Novel Approaches for Regional Multifocus Image Fusion [chapter]

Long Chen, Junwei Duan, C.L. Philip Chen
2016 Recent Advances in Image and Video Coding  
Existing research in multifocus image fusion tends to emphasis on the pixel-level image fusion using transform domain methods.  ...  In this chapter, we provide an overview of regional multi-focus image fusion, and two different orthogonal matching pursuitbased sparse representation methods are adopted for regional multi-focus image  ...  In the following section, we first introduce on how to express the image patches using two kinds of sparse representation algorithms: orthogonal matching pursuit (OMP) algorithm and simultaneous orthogonal  ... 
doi:10.5772/65076 fatcat:mpkj7tg5b5anbb6ln3bh36uebu

Image fusion via nonlocal sparse K-SVD dictionary learning

Ying Li, Fangyi Li, Bendu Bai, Qiang Shen
2016 Applied Optics  
The performance of the NL_SK_SVD dictionary is applied for image fusion using simultaneous orthogonal matching pursuit.  ...  The proposed approach is evaluated with different types of image, and compared with a number of alternative image fusion techniques.  ...  In particular, the fusion process is implemented with the simultaneous orthogonal matching pursuit (SOMP) procedure [39] , guaranteeing that different source images are sparsely decomposed into the same  ... 
doi:10.1364/ao.55.001814 pmid:26974648 fatcat:elkd66egtbh35jwj2cbxnmysem

Multi-Feature Joint Sparse Model for the Classification of Mangrove Remote Sensing Images

Yan-Min Luo, Yi Ouyang, Ren-Cheng Zhang, Hsuan-Ming Feng
2017 ISPRS International Journal of Geo-Information  
and their eight neighborhood pixels is proposed to represent the spatial correlation of neighboring pixels, which can make good use of the spatial correlation of adjacent pixels.  ...  the similar spectral features between mangroves and other land cover types, challenges are posed since the accuracy is sometimes unsatisfactory in distinguishing mangroves from other land cover types with  ...  At present, the common methods include base pursuit (BP) [16] , orthogonal matching pursuit (OMP) [17] , simultaneous orthogonal matching pursuit (SOMP) [18] , and so on.  ... 
doi:10.3390/ijgi6060177 fatcat:mozsetkqkjathld3xnfyjcoixm

LDA Feature Selection for Satellite Image Fusion in HAAR Wavelet

2016 International Journal of Science and Research (IJSR)  
First discrete wavelet transform (DWT) for time to frequency conversion, feature extraction, feature selection based on LDA and finally classify the feature level fusion.  ...  spatial and high spectral resolutions simultaneously.  ...  Sparse representation of signals is now possible utilizing many different Greedy approaches including Matching Pursuit, Orthogonal Matching Pursuit.  ... 
doi:10.21275/v5i4.nov162737 fatcat:d3dklluhgzctrdxhw5pzwav34a

Spectral Representation vis Data-Guided Sparsity for Hyperspectral Image Super-Resolution†

Xian-Hua Han, YongQing Sun, Jian Wang, Boxin Shi, YinQiang Zheng, Yen-Wei Chen
2019 Sensors  
Given the RGB vector and the RGB dictionary, the sparse representation of each pixel in the high resolution image is calculated with the guidance of a sparsity map, which measures pixel material purity  ...  We propose a novel hyperspectral image superresolution method via non-negative sparse representation of reflectance spectra with a data guided sparsity constraint.  ...  simultaneous orthogonal matching pursuit (G-SOMP+) method for estimating the sparse coefficients.  ... 
doi:10.3390/s19245401 fatcat:uwbtp5ycyfb3joqg642xii6eea

A New Robust Adaptive Fusion Method for Double-Modality Medical Image PET/CT

Tao Zhou, Huiling Lu, Fuyuan Hu, Hongbin Shi, Shi Qiu, Huiqun Wang, Andrea Scribante
2021 BioMed Research International  
The high-frequency measurement value is fused according to the fusion factor, and high-frequency fusion image is reconstructed by using the orthogonal matching pursuit algorithm of the high-frequency measurement  ...  To validate the proposed algorithm, four comparative experiments were performed: comparative experiment with other image fusion algorithms, comparison of different activity measures, different match measures  ...  reconstructed by using the orthogonal matching pursuit algorithm of the high-frequency measurement.  ... 
doi:10.1155/2021/8824395 fatcat:ppp56hsg6ngktftxfdmmtnoeom


S. Srinivasan, Dr. K. Rajakumar
2017 International Journal on Smart Sensing and Intelligent Systems  
For each test pixel, the class label is determined with the help of obtained coefficients.  ...  The spectral and spatial information reflected from the original Hyperspectral Images with four various features.  ...  Sparse Representation Classification (SRC) To overcome the problem of optimization, the various pursuit methods are Basis pursuit [149] , orthogonal matching pursuit [150] , matching pursuit [151] ,  ... 
doi:10.21307/ijssis-2017-224 fatcat:k2x24hgfkjctxh3jwjssq5esle

Annular Spatial Pyramid Mapping and Feature Fusion-Based Image Coding Representation and Classification

Mengxi Xu, Yingshu Lu, Xiaobin Wu
2020 Wireless Communications and Mobile Computing  
Aiming to solve this problem, this paper proposes a feature fusion-based image classification model.  ...  At the stage of feature fusion, we adopt a support vector machine with two kernels (SVM-2K) algorithm, which divides the training process into two stages and finally learns the knowledge from the corresponding  ...  Acknowledgments This work is supported partly by the University-Level Research Fund Project of Nanjing Institute of Technology (No. ZKJ201907).  ... 
doi:10.1155/2020/8838454 fatcat:a4wz3hsldfa5hivc6hk737l7uu

Exploiting process integration and composition in the context of active vision

J.A. Fayman, P. Pirjanian, H.I. Christensen, E. Rivlin
1999 IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)  
We have experimented with the fusion of four smooth pursuit techniques, such as template matching and image differencing.  ...  Secondly, we address the issue of integration in the active vision activity of smooth pursuit.  ...  The template matching algorithm compares the template with the image at different image locations and finds the location in the image that best matches the template.  ... 
doi:10.1109/5326.740671 fatcat:he3lvr7wgveljidtf7isrgy3xi

Application of Morphological Component Analysis to Optical Image Fusion

Georges Laussane Loum, Atiampo Kodjo Armand, Pandry Koffi Ghislain, Souleymane Oumtanaga
2017 American Journal of Applied Sciences  
In this study, we propose a new model of images fusion with very high spatial resolution.  ...  Finally the image fusion is obtained through linear combination of merged smooth and texture components.  ...  However, this new approach is limited the one hand by the complexity of implementation of algorithms used (Basis Pursuit, Orthogonal Matching Pursuit, Chambolle-Pock) and on the other hand limited by the  ... 
doi:10.3844/ajassp.2017.795.807 fatcat:2pym7p4mtjaavgsajcrqeupniu

Multisensor Fusion of Landsat Images for High-Resolution Thermal Infrared Images Using Sparse Representations

Hong Sung Jin, Dongyeob Han
2017 Mathematical Problems in Engineering  
We then compare the fused images created with different sampling factors and patch sizes.  ...  The results of both qualitative and quantitative evaluation show that the proposed method improves spatial resolution and preserves the thermal properties of basic LST data for use with environmental problems  ...  It is an NP-hard problem, and it has several methods for approximation such as basis pursuit (BP) and orthogonal matching pursuit (OMP) [18] .  ... 
doi:10.1155/2017/2048098 fatcat:525bjrtxkzg7jl3tjmuhxjjvie

Hybrid matching pursuit for distributed through-wall radar imaging

Gang Li, Robert J. Burkholder
2015 IEEE Transactions on Antennas and Propagation  
In TWRI applications, existing distributed greedy algorithms such as the simultaneous orthogonal matching pursuit (SOMP) algorithm and the simultaneous subspace pursuit (SSP) algorithm suffer from high  ...  In this paper, we consider the problem of throughwall radar imaging (TWRI) with an antenna array and develop a distributed greedy algorithm named hybrid matching pursuit (HMP).  ...  In [24] , the TWRI is accomplished by a MMV-based greedy algorithm named the simultaneous orthogonal matching pursuit (SOMP) [29] , [30] .  ... 
doi:10.1109/tap.2015.2398115 fatcat:hpdbqdmxdfck3eq6wh5xpz36pu

Sparse Representations-Based Super-Resolution of Key-Frames Extracted from Frames-Sequences Generated by a Visual Sensor Network

Muhammad Sajjad, Irfan Mehmood, Sung Baik
2014 Sensors  
OOMP does better in terms of detecting true sparsity than orthogonal matching pursuit (OMP). This property of the OOMP helps produce a HR image which is closer to the original image.  ...  The proposed SR scheme uses optimized orthogonal matching pursuit (OOMP) for sparse-representation recovery in SR.  ...  Batch-OMP is a good option to handle a large set of training signals than a simple orthogonal matching pursuit (OMP).  ... 
doi:10.3390/s140203652 pmid:24566632 pmcid:PMC3958298 fatcat:zou3sq7ksnbmtkue4lsqj6iyqm
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