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Expressive Spectral Error Visualization for Enhanced Spectral Unmixing [article]

Björn Labitzke, Frank Urrigshardt, Andreas Kolb
2013 International Symposium on Vision, Modeling, and Visualization  
Our visual analysis approach comprises different techniques for an expressive spectral error visualization, efficiently guiding the user towards spectra in the dataset which are potentially missing materials  ...  Even though many automatic methods for spectral unmixing exist, in many practical applications, domain experts have to verify the result and sometimes have to manually adjust the set of determined materials  ...  In this paper, we propose a novel visual analysis approach to enhance LSU-results by expressive spectral error visualization to efficiently guide a user to specific spectra for local exploration.  ... 
doi:10.2312/pe.vmv.vmv13.009-016 dblp:conf/vmv/LabitzkeUK13 fatcat:r3tkndk2d5akfpnqjzul7ljhym

Generic visual analysis for multi- and hyperspectral image data

Björn Labitzke, Serkan Bayraktar, Andreas Kolb
2012 Data mining and knowledge discovery  
An adequate system feedback of the costly unmixing procedure for the spectral data with respect to the current set of endmembers is ensured by a novel technique for progressive unmixing and view update  ...  visual analysis by means of visual exploration.  ...  Furthermore, the Raman datasets are kindly provided by the Research Group for High Frequency and Quantum Electronics at the University of Siegen.  ... 
doi:10.1007/s10618-012-0283-9 fatcat:rbyataemhzbf7apbulbjy7b6la

Evaluation of Two Applications of Spectral Mixing Models to Image Fusion

Gary D. Robinson, Harry N. Gross, John R. Schott
2000 Remote Sensing of Environment  
Image Merging for Enhancement of Visual Display Image fusion routines that enhance visual display have also been referred to as ad hoc methods.  ...  If applications requiring visually enhanced fraction maps are desired, then the fuse/unmix process is the obvious choice.  ...  The stepwise unmixing routine proceeds as follows: 1. Read "header" information. Program: get_data.pro.  ... 
doi:10.1016/s0034-4257(99)00074-7 fatcat:qk6jgbpcyfhbtg2k77tkxbf43m

Multiplicative Iterative Nonlinear Constrained Coupled Non-negative Matrix Factorization (MINC-CNMF) for Hyperspectral and Multispectral Image Fusion

Priya K, Rajkumar K K
2021 International Journal of Advanced Computer Science and Applications  
This method not only consider the spatial quality but also enhance the spectral data by imposing constraints known as minimum volume (MV) which helps to estimate accurate endmembers.  ...  To overcome this limitation, we are going to propose an unmixing based fusion algorithm namely Multiplicative Iterative Nonlinear Constrained Coupled Nonnegative Matrix Factorization (MINC-CNMF) that enhance  ...  ACKNOWLEDGMENT The authors would like to express the gratitude to all the reviewers for their helpful comments and suggestions to improve the quality of paper.  ... 
doi:10.14569/ijacsa.2021.0120660 fatcat:bmpvh3vwubdq5hwebyuqmof7pq

Gated Autoencoder Network for Spectral–Spatial Hyperspectral Unmixing

Ziqiang Hua, Xiaorun Li, Jianfeng Jiang, Liaoying Zhao
2021 Remote Sensing  
Convolution-based autoencoder networks have yielded promising performances in exploiting spatial–contextual signatures for spectral unmixing.  ...  This study confirms the effectiveness of gating mechanism in improving the accuracy and efficiency of utilizing spatial signatures for spectral unmixing.  ...  Spectral unmixing generally only considers spectral information for processing, and the process of unmixing different pixels is independent.  ... 
doi:10.3390/rs13163147 fatcat:snphfepgn5af5pxbjnb2dhqye4

Hyperspectral Image Resolution Enhancement Approach Based on Local Adaptive Sparse Unmixing and Subpixel Calibration

Yidan Teng, Ye Zhang, Chunli Ti, Junping Zhang
2018 Remote Sensing  
Unmixing based fusion aims at generating a high spectral-spatial resolution image (HSS) with the same surface features of the high spatial resolution multispectral image (MS) and low spatial resolution  ...  First, we put forward a local adaptive sparse unmixing based fusion (LASUF) algorithm, in which the sparsity of the abundance matrices is appended as the constraint to the optimization fusion, considering  ...  The authors also want to thank Naoto Yokoya for the CNMF algorithm code, Qi Wei for the Bayesian algorithm code and Dong for the NSSR algorithm code.  ... 
doi:10.3390/rs10040592 fatcat:3lskz6ognbfuze3dav5vjdo5ua

Least Angle Regression-Based Constrained Sparse Unmixing of Hyperspectral Remote Sensing Imagery

Ruyi Feng, Lizhe Wang, Yanfei Zhong
2018 Remote Sensing  
In this paper, to improve the regression accuracy of sparse unmixing, least angle regression-based constrained sparse unmixing (LARCSU) is introduced to further enhance the precision of sparse unmixing  ...  Since the potentially large standard spectral library can be given a priori, the most challenging task is to compute the regression coefficients, i.e., the fractional abundances, for the linear regression  ...  Ma for sharing their latest sparse unmixing algorithm source code and their good suggestions as to how we could improve our paper.  ... 
doi:10.3390/rs10101546 fatcat:xwd7iifshnfnned4v6eny73gge

Fast Hyperspectral Unmixing via Reweighted Sparse Regression

Hongwei HAN, Ke GUO, Maozhi WANG, Tingbin ZHANG, Shuang ZHANG
2019 IEICE transactions on information and systems  
However, the high mutual coherence of spectral libraries strongly affects the practicality of sparse unmixing.  ...  For the real hyperspectral datasets, the pruned spectral library successfully reduces the original dictionary size by 76% and the runtime of the proposed algorithm is 11.21% of that of CLSUnSAL.  ...  For instance, enhancing spectral unmixing using local neighborhood weights [36] was developed to utilize both spectral information and spatial information.  ... 
doi:10.1587/transinf.2018edp7374 fatcat:skpwmrpaf5dqdoqm3g5yvtqiye

A new tool for variable multiple endmember spectral mixture analysis (VMESMA)

F. J. García‐Haro, S. Sommer, T. Kemper
2005 International Journal of Remote Sensing  
In this paper we present a computing and environmental analysis tool, named VMESMA, which extends the possibilities of conventional spectral unmixing.  ...  Spectral mixture analysis is a widely used method to determine the sub-pixel abundance of vegetation, soils and other spectrally distinct materials that fundamentally contribute to the spectral signal  ...  Special thanks are due to the anonymous reviewers for their extremely helpful suggestions.  ... 
doi:10.1080/01431160512331337817 fatcat:6zytol2cljgirpsldqsvgtuzr4

Supplementary document for Hyperspectral multiphoton microscopy for in vivo visualization of multiple, spectrally-overlapped fluorescent labels - 4445260.pdf

Amanda Bares, Menansili Mejooli, Mitchell Pender, Scott Leddon, Steven Tilley, Karen Lin, Jingyuan Dong, Minsoo Kim, Deborah Fowell, Nozomi Nishimura
2020 figshare.com  
Unmixed images for HeLa cells expressing only one fusion construct and used as single-color images for spectral end-member selection.  ...  Images were unmixed and the GFP-microglia channel selected for visualization of microglia structure.  ... 
doi:10.6084/m9.figshare.13034195.v2 fatcat:5jjmgb3nyvgozgtjzs62wnrykm

Superpixel-Based Weighted Collaborative Sparse Regression and Reweighted Low-Rank Representation for Hyperspectral Image Unmixing

Hongjun Su, Cailing Jia, Pan Zheng, Qian Du
2021 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
However, the imprecise spatial contextual information, the lack of global feature and the high mutual coherences of a spectral library greatly limit the performance of sparse unmixing.  ...  low-rank representation unmixing (SBWCRLRU).  ...  Inspired by [23] , [50] , [51] , sparse unmixing is performed while considering the additional constraint provided by weighting to enhance the sparsity of abundance vector in the spectral domains.  ... 
doi:10.1109/jstars.2021.3133428 fatcat:pbbag6efkjdphgswkyz22x6ch4

Supplementary document for Hyperspectral multiphoton microscopy for in vivo visualization of multiple, spectrally-overlapped fluorescent labels - 4445260.pdf

Amanda Bares, Menansili Mejooli, Mitchell Pender, Scott Leddon, Steven Tilley, Karen Lin, Jingyuan Dong, Minsoo Kim, Deborah Fowell, Nozomi Nishimura
2020 figshare.com  
Unmixed images for HeLa cells expressing only one fusion construct and used as single-color images for spectral end-member selection.  ...  Images were unmixed and the GFP-microglia channel selected for visualization of microglia structure.  ... 
doi:10.6084/m9.figshare.13034195.v1 fatcat:p35rrgu7kfabfgqqv6u44oo2da

Mapping alteration minerals using sub-pixel unmixing of ASTER data in the Sarduiyeh area, SE Kerman, Iran

Mahdieh Hosseinjani, Majid H. Tangestani
2011 International Journal of Digital Earth  
Acknowledgements We would like to thank the Australian Geological and Remote Sensing Services (AGARSS) for spectral analysis of rock samples.  ...  The results of spectral unmixing appear as a series of gray-scale images, one for each endmember, plus a root-mean-square (RMS) error image.  ...  Accuracy assessment Classification error matrix or confusion matrix is one of the most commonly used methods for expressing classification accuracy (Congalton 1991) .  ... 
doi:10.1080/17538947.2010.550937 fatcat:m3rdj3ltz5djbiaaz2wvvnedmm

Near-Infrared Bioluminescence Imaging of Macrophage Sensors for Cancer Detection In Vivo

Giorgia Zambito, Gunja Mishra, Christopher Schliehe, Laura Mezzanotte
2022 Frontiers in Bioengineering and Biotechnology  
cells were instead engineered to express a near-infrared click beetle luciferase (CBR2).  ...  The early detection of malignant melanoma is critical for effective therapy. Because melanoma often resembles moles, routine skin check-up may help for timely identification of suspicious areas.  ...  The filter selected for the green spectral unmixing (BMC2-CBG2) was set at 700 nm, and for the magenta spectral unmixing (B16-CBR2), the filter was set at 740 nm.  ... 
doi:10.3389/fbioe.2022.867164 pmid:35615475 pmcid:PMC9124759 fatcat:6eupyny3njfbhjbj5tqsavobo4

Enhancing spectral unmixing by considering the point spread function effect

Qunming Wang, Wenzhong Shi, Peter M. Atkinson
2018 Spatial Statistics  
., Enhancing spectral unmixing by considering the point spread function effect. Spatial Statistics (2018), https://doi.  ...  In this paper, a new method is proposed to account for 21 the PSF effect within spectral unmxing to produce more accurate predictions of land cover 22 30 31  ...  ., 2006) . 400 However, this paper aims to find a solution to account for the PSF effect to enhance spectral 401 unmixing predictions.  ... 
doi:10.1016/j.spasta.2018.03.003 fatcat:ztvcps3sord5xh2qhg7p56lbxa
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