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A Manifold Alignment Approach for Hyperspectral Image Visualization With Natural Color
2016
IEEE Transactions on Geoscience and Remote Sensing
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In this paper, we propose a new framework for visualizing hyperspectral image with natural color by fusion of a hyperspectral image and a high-resolution color image via manifold alignment. ...
In this way, a visualized image with natural color distribution and fine spatial details can be generated. Another advantage of the proposed method is its flexible data setting for various scenarios. ...
CONCLUSIONS We have presented a new approach to visualize HSIs with natural color. ...
doi:10.1109/tgrs.2015.2512659
fatcat:qvzj2jrl45bzzfqh7565imzqky
Visualization of hyperspectral imagery based on manifold learning
2013
2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS
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At the second stage, we transfer the natural color of a panchromatic image to the image obtained by the first step via manifold alignment. ...
Experimental results show that the visualized image not only retains the structure of the hyperspectral image but also possesses natural colors. ...
Second, color transfer is performed based on manifold alignment. The pseudo-color image is aligned with a corresponding panchromatic image to adjust the pseudo color to natural color. ...
doi:10.1109/igarss.2013.6723196
dblp:conf/igarss/LiaoYJQ13a
fatcat:l5slvezn4nacdmw674uvhm4jie
Visualization of Hyperspectral Imaging Data Based on Manifold Alignment
2014
2014 22nd International Conference on Pattern Recognition
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color and spatial information of a high-resolution color image to a hyperspectral image to generate a visualized image with natural color distribution and finer details. ...
Previous visualization approaches focused on preserving as much information as possible in the reduced spectral space, but ended up with displaying hyperspectral images as false color images, which contradicts ...
In this paper, we propose a HSI visualization method based on manifold alignment with the aid of a high resolution color image (HRCI). ...
doi:10.1109/icpr.2014.22
dblp:conf/icpr/LiaoQZ14
fatcat:4qizbowm3fckfo4arjpusoatli
Constrained Manifold Learning for Hyperspectral Imagery Visualization
[article]
2017
arXiv
pre-print
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In this paper, we propose a visualization approach based on constrained manifold learning, whose goal is to learn a visualized image that not only preserves the manifold structure of the HSI but also has ...
Manifold learning preserves the image structure by forcing pixels with similar signatures to be displayed with similar colors. ...
We previously proposed a manifold alignment method to visualize HSI with natural colors [23] . ...
arXiv:1712.01657v1
fatcat:2prj2mugvvc5fedb7gce43o4jq
Spectral Image Visualization Using Generative Adversarial Networks
[article]
2018
arXiv
pre-print
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In this paper, we present a novel visualization generative adversarial network (GAN) to display spectral images in natural colors. ...
The adversarial loss pushes our solution to the natural image distribution using a discriminator network that is trained to differentiate between false-color images and natural-color images. ...
Liao et al. utilized manifold alignment to transfer colors from natural RGB images to hyperspectral images [8] - [10] . ...
arXiv:1802.02290v1
fatcat:nkvnxerpdfg77ejltckbpdxnlq
An Object-Oriented Color Visualization Method with Controllable Separation for Hyperspectral Imagery
2020
Applied Sciences
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In this paper, an object-oriented hyperspectral color visualization approach with controllable separation is proposed. ...
Most of the available hyperspectral image (HSI) visualization methods can be considered as data-oriented approaches. ...
Landgrebe from Purdue University for providing the AVIRIS Indian Pines data set and Prof. P. Gamba from the University of Pavia for providing the ROSIS-3 University of Pavia data set. ...
doi:10.3390/app10103581
fatcat:yv5v4ddkjngovmtp5icu6pne44
Visualization of Hyperspectral Images Using Moving Least Squares
[article]
2018
arXiv
pre-print
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In this paper, we propose a nonlinear approach to visualize an input HSI with natural colors by taking advantage of a corresponding RGB image. ...
The matching pixels between a pair of HSI and RGB image can be reused to display other HSIs captured b the same imaging sensor with natural colors. ...
[12] proposed an approach to display HSIs with natural colors based on manifold alignment between arXiv:1801.06635v1 [cs.CV] 20 Jan 2018 an HSI and a high resolution RGB image. ...
arXiv:1801.06635v1
fatcat:p33nl72tt5cybgs5p7vy7vqcum
Exploiting manifold geometry in hyperspectral imagery
2005
IEEE Transactions on Geoscience and Remote Sensing
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This new approach seeks a manifold coordinate system that preserves geodesic distances in the high-dimensional hyperspectral data space. ...
Additionally, we demonstrate that this technique provides a natural data compression scheme, which dramatically reduces the number of components needed to model hyperspectral data when compared with traditional ...
However, the tiling approach employed here with well-defined tile boundaries permits an easy, visual analysis of the continuity of the manifold results across tile boundaries.
IX. ...
doi:10.1109/tgrs.2004.842292
fatcat:mqhoprk7dffm7daplzymyymrzm
Adversarial Networks for Scale Feature-Attention Spectral Image Reconstruction from a Single RGB
2020
Sensors
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Hyperspectral images reconstruction focuses on recovering the spectral information from a single RGBimage. ...
We first propose scale attention pyramid UNet (SAPUNet), which uses U-Net with dilated convolution to extract features. ...
We used this GAN-based algorithm to learn a generative model of the joint spectro-spatial distribution of the data manifold of natural hyperspectral images. ...
doi:10.3390/s20082426
pmid:32344686
pmcid:PMC7219499
fatcat:h4gcdz6zsjbo3bzbbj7f75ifma
Local detail enhanced hyperspectral image visualization
2015
2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
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A new method for hyperspectral image (HSI) visualization is proposed in this paper, which emphasizes on pairwise distance preservation and detail enhancement. It includes two sequential steps. ...
The proposed HSI visualization method takes the global and local information of spectral and spatial distribution in HSI into account for visualization, which makes the color display of HSI carry as much ...
In [2] , the feature-level semisupervised manifold alignment is used to transfer the RGB information of a color image to a HSI over the same scene, so that a natural dispaly of HSI can be obtained. ...
doi:10.1109/igarss.2015.7325960
dblp:conf/igarss/FangQ15
fatcat:br7v7oyvlfhqbb7k6shnwr5sl4
Intraoperative Assessment of Tumor Margins in Tissue Sections with Hyperspectral Imaging and Machine Learning
2022
Cancers
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With this, we introduce HSI in combination with ML hyperspectral imaging as a potential new tool for intraoperative tumor margin assessment. ...
Optical methods such as hyperspectral imaging (HSI) are therefore of high interest to overcome these limitations. ...
Visualization as False Color Images for Tumor Classification To visually inspect the hyperspectral datacubes, we performed an unsupervised nonlinear dimensionality reduction using uniform manifold approximation ...
doi:10.3390/cancers15010213
pmid:36612208
pmcid:PMC9818424
fatcat:hwiqasmvfzh6xhnz4rscwdio5a
Perception-Based Visualization of Manifold-Valued Medical Images Using Distance-Preserving Dimensionality Reduction
2011
IEEE Transactions on Medical Imaging
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A method for visualizing manifold-valued medical image data is proposed. The method operates on images in which each pixel is assumed to be sampled from an underlying manifold. ...
DT or TAC pixels) with perceptually similar colors. ...
In this work we address these issues by proposing a visualization approach for high-dimensional, manifold-valued medical image data that (a) is faithful to the underlying medical image data; (b) respects ...
doi:10.1109/tmi.2011.2111422
pmid:21296705
fatcat:ih3eocdl4jctha6lhnppngo7ae
Adversarial Networks for Spatial Context-Aware Spectral Image Reconstruction from RGB
2017
2017 IEEE International Conference on Computer Vision Workshops (ICCVW)
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Quantitative evaluation shows a Root Mean Squared Error (RMSE) drop of 33.2% and a Relative RMSE drop of 54.0% on the ICVL natural hyperspectral image dataset. ...
We pose hyperspectral natural image reconstruction as an image to image mapping learning problem, and apply a conditional generative adversarial framework to help capture spatial semantics. ...
We depart from a database of perfectly aligned RGB and hyperspectral image pairs, which are extracted one pair at a time. ...
doi:10.1109/iccvw.2017.64
dblp:conf/iccvw/Alvarez-GilaWG17
fatcat:dpqktzlec5extl627mfpm3ap7e
Spectral 3D Computer Vision – A Review
[article]
2023
arXiv
pre-print
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This survey offers a comprehensive overview of spectral 3D computer vision, including a unified taxonomy of methods, key application areas, and future challenges and prospects. ...
Mapping the spectral information onto the 3D model reveals changes in the spectra-structure space or enhances 3D representations with properties such as reflectance, chromatic aberration, and varying defocus ...
To this end, hyperspectral images shall be first rectified and aligned with RGB images. ...
arXiv:2302.08054v1
fatcat:ygtb53kstfadti3yo367ips53y
The Role of Hyperspectral Imaging: A Literature Review
2018
International Journal of Advanced Computer Science and Applications
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Optical analysis techniques are used recently to detect and identify the objects from a large scale of images. Hyperspectral imaging technique is also one of them. ...
The proposed idea can be useful for further research in the field of hyperspectral imaging using deep learning. ...
[21] proposed method to visualize hyperspectral image in normal color by the coordination of HSI and high resolution image through multiple alignments. ...
doi:10.14569/ijacsa.2018.090808
fatcat:54bc7yptrrddhcqd4snkbkuxna
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