Výsledky vyhledávání - "Peter W. T. Yuen"

Akademický článek

Signal to Noise Ratio of a Coded Slit Hyperspectral Sensor

Autor: Jonathan Piper, Peter W. T. Yuen, David James

Publikováno v: Signals, Vol 3, Iss 4, Pp 752-764 (2022)

In recent years, a wide range of hyperspectral imaging systems using coded apertures have been proposed. Many implement compressive sensing to achieve faster acquisition of a hyperspectral data cube, but it is also potentially beneficial to use coded

Externí odkaz: https://doaj.org/article/abef773620204863bda61bdd73f9d1ea

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Akademický článek

An End-to-End Hyperspectral Scene Simulator with Alternate Adjacency Effect Models and Its Comparison with CameoSim

Autor: Usman A. Zahidi, Peter W. T. Yuen, Jonathan Piper, Peter S. Godfree

Publikováno v: Remote Sensing, Vol 12, Iss 1, p 74 (2019)

In this research, we developed a new rendering-based end to end Hyperspectral scene simulator CHIMES (Cranfield Hyperspectral Image Modelling and Evaluation System), which generates nadir images of passively illuminated 3-D outdoor scenes in Visible,

Externí odkaz: https://doaj.org/article/f33e1b483f954cc2b8fb8ae88453e665

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Akademický článek

Endmember Learning with K-Means through SCD Model in Hyperspectral Scene Reconstructions

Autor: Ayan Chatterjee, Peter W. T. Yuen

Publikováno v: Journal of Imaging, Vol 5, Iss 11, p 85 (2019)

This paper proposes a simple yet effective method for improving the efficiency of sparse coding dictionary learning (DL) with an implication of enhancing the ultimate usefulness of compressive sensing (CS) technology for practical applications, such

Externí odkaz: https://doaj.org/article/556744a763aa4a73b0d5e7d1e1e32c9e

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Akademický článek

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Sample Selection with SOMP for Robust Basis Recovery in Sparse Coding Dictionary Learning

Autor: Peter W. T. Yuen, Ayan Chatterjee

Publikováno v: IEEE Letters of the Computer Society. 2:28-31

Sparse Coding Dictionary (SCD) learning is to decompose a given hyperspectral image into a linear combination of a few bases. In a natural scene, because there is an imbalance in the abundance of materials, the problem of learning a given material we

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::21bcd2f448e1f6350d8f0c2c29b7e999
https://doi.org/10.1109/locs.2019.2938446

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Remote sensing image fusion via compressive sensing

Autor: Ardhendu Behera, Morteza Ghahremani, Yonghuai Liu, Peter W. T. Yuen

Publikováno v: ISPRS Journal of Photogrammetry and Remote Sensing. 152:34-48

In this paper, we propose a compressive sensing-based method to pan-sharpen the low-resolution multispectral (LRM) data, with the help of high-resolution panchromatic (HRP) data. In order to successfully implement the compressive sensing theory in pa

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b2a7d733d0909539cadc54154c006310
https://doi.org/10.1016/j.isprsjprs.2019.04.001

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Novel Gumbel-Softmax trick enabled concrete autoencoder with entropy constraints for unsupervised hyperspectral band selection

Autor: He Sun, Huimin Zhao, Jinchang Ren, Julius Tschannerl, Peter W. T. Yuen

As an important topic in hyperspectral image (HSI) analysis, band selection has attracted increasing attention in the last two decades for dimensionality reduction in HSI. With the great success of deep learning (DL)-based models recently, a robust u

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1571571de35173ad5ea67d23a98ec31f
http://dspace.lib.cranfield.ac.uk/handle/1826/16877

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Automatic Extraction of Material Defect Size by Infrared Image Sequence

Autor: Xiao Zhu, Peter W. T. Yuen, Quanbin Sun, Lihua Yuan, Haibo Liu, Yonghuai Liu

Publikováno v: Applied Sciences, Vol 10, Iss 8248, p 8248 (2020)
Applied Sciences
Volume 10
Issue 22

A typical pulsed thermography procedure results in a sequence of infrared images that reflects the evolution of temperature over time. Many features of defects, such as shape, position, and size, are derived from single image by image processing. Hen

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::49208ac1f156851e107513bfe6a822ed
https://www.mdpi.com/2076-3417/10/22/8248

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Rapid Estimation of Orthogonal Matching Pursuit Representation

Autor: Ayan Chatterjee, Peter W. T. Yuen

Publikováno v: IGARSS

Orthogonal Matching Pursuit (OMP) has proven itself to be a significant algorithm in image and signal processing domain in the last decade to estimate sparse representations in dictionary learning. Over the years, efforts to speed up the OMP algorith

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ec3a8337b4fca0940e644fa01d1072ba
https://doi.org/10.1109/igarss39084.2020.9323532

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Spatial spectral band selection for enhanced hyperspectral remote sensing classification applications

Autor: Peter Godfree, Chris McCullough, Changfeng Yuan, Ruben Moya Torres, Peter W. T. Yuen, Johathan Piper

Publikováno v: Journal of Imaging
Volume 6
Issue 9
Journal of Imaging, Vol 6, Iss 87, p 87 (2020)

Despite the numerous band selection (BS) algorithms reported in the field, most if not all have exhibited maximal accuracy when more spectral bands are utilized for classification. This apparently disagrees with the theoretical model of the &lsquo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8c23747524e42667d7eaac620bc87355
http://dspace.lib.cranfield.ac.uk/handle/1826/16017

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