scholarly journals Hyper-Spectral Imaging Technique in the Cultural Heritage Field: New Possible Scenarios

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2843 ◽  
Author(s):  
Marcello Picollo ◽  
Costanza Cucci ◽  
Andrea Casini ◽  
Lorenzo Stefani
Keyword(s):  
Cultural Heritage ◽  
Hyperspectral Imaging ◽  
Imaging System ◽  
Imaging Techniques ◽  
Imaging Spectroscopy ◽  
Spectral Imaging ◽  
Imaging Data ◽  
Spectroscopic Information ◽  
Hyper Spectral Imaging ◽  
Recent Developments

Imaging spectroscopy technique was introduced in the cultural heritage field in the 1990s, when a multi-spectral imaging system based on a Vidicon camera was used to identify and map pigments in paintings. Since then, with continuous improvements in imaging technology, the quality of spectroscopic information in the acquired imaging data has greatly increased. Moreover, with the progressive transition from multispectral to hyperspectral imaging techniques, numerous new applicative perspectives have become possible, ranging from non-invasive monitoring to high-quality documentation, such as mapping and characterization of polychrome and multi-material surfaces of cultural properties. This article provides a brief overview of recent developments in the rapidly evolving applications of hyperspectral imaging in this field. The fundamentals of the various strategies, that have been developed for applying this technique to different types of artworks are discussed, together with some examples of recent applications.

scholarly journals Comparison of spectral selection methods in the development of classification models from visible near infrared hyperspectral imaging data

2019 ◽  
Author(s):  
Aoife Gowen ◽  
Jun-Li Xu ◽  
Ana Herrero-Langreo
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Spatial Information ◽  
Hyperspectral Image ◽  
Imaging Spectroscopy ◽  
Model Performance ◽  
Data Sampling ◽  
Classification Models ◽  
Imaging Data ◽  
Selection Of

Applications of hyperspectral imaging (HSI) to the quantitative and qualitative measurement of samples have grown widely in recent years, due mainly to the improved performance and lower cost of imaging spectroscopy instrumentation. Data sampling is a crucial yet often overlooked step in hyperspectral image analysis, which impacts the subsequent results and their interpretation. In the selection of pixel spectra for the calibration of classification models, the spatial information in HSI data can be exploited. In this paper, a variety of sampling strategies for selection of pixel spectra are presented, exemplified through five case studies. The strategies are compared in terms of the proportion of global variability captured, practicality and predictive model performance. The use of variographic analysis as a guide to the spatial segmentation prior to sampling leads to the selection of representative subsets while reducing the variation in model performance parameters over repeated random selection.

Design of a Hyper-Spectral Imaging System for Gross Pathology of Pigmented Skin Lesions

2021 ◽  
Author(s):  
Eleni Aloupogianni ◽  
Masahiro Ishikawa ◽  
Takaya Ichimura ◽  
Atsushi Sasaki ◽  
Naoki Kobayashi ◽  
...  
Keyword(s):  
Imaging System ◽  
Spectral Imaging ◽  
Skin Lesions ◽  
Gross Pathology ◽  
Hyper Spectral ◽  
Hyper Spectral Imaging ◽  
Pigmented Skin Lesions

scholarly journals POTENTIAL OF AIRBORNE IMAGING SPECTROSCOPY AT CZECHGLOBE

2016 ◽  
Vol XLI-B1 ◽  
pp. 15-17 ◽  
Author(s):  
J. Hanuš ◽  
T. Fabiánek ◽  
L. Fajmon
Keyword(s):  
Remote Sensing ◽  
Hyperspectral Imaging ◽  
Laser Scanning ◽  
Imaging System ◽  
Spectral Response ◽  
Imaging Spectroscopy ◽  
Laser Scanner ◽  
Current Status ◽  
Functional Changes ◽  
Processing Chain

Ecosystems, their services, structures and functions are affected by complex environmental processes, which are both natural and human-induced and globally changing. In order to understand how ecosystems behave in globally changing environment, it is important to monitor the current status of ecosystems and their structural and functional changes in time and space. An essential tool allowing monitoring of ecosystems is remote sensing (RS). Many ecosystems variables are being translated into a spectral response recorded by RS instruments. It is however important to understand the complexity and synergies of the key ecosystem variables influencing the reflected signal. This can be achieved by analysing high resolution RS data from multiple sources acquired simultaneously from the same platform. Such a system has been recently built at CzechGlobe - Global Change Research Institute (The Czech Academy of Sciences). <br><br> CzechGlobe has been significantly extending its research infrastructure in the last years, which allows advanced monitoring of ecosystem changes at hierarchical levels spanning from molecules to entire ecosystems. One of the CzechGlobe components is a laboratory of imaging spectroscopy. The laboratory is now operating a new platform for advanced remote sensing observations called FLIS (Flying Laboratory of Imaging Spectroscopy). FLIS consists of an airborne carrier equipped with passive RS systems. The core instrument of FLIS is a hyperspectral imaging system provided by Itres Ltd. The hyperspectral system consists of three spectroradiometers (CASI 1500, SASI 600 and TASI 600) that cover the reflective spectral range from 380 to 2450 nm, as well as the thermal range from 8 to 11.5 μm. The airborne platform is prepared for mounting of full-waveform laser scanner Riegl-Q780 as well, however a laser scanner is not a permanent part of FLIS. In 2014 the installation of the hyperspectral scanners was completed and the first flights were carried out with all sensors. <br><br> The new hyperspectral imaging system required adaptations in the data pre-processing chain. The established pre-processing chain (radiometric, atmospheric and geometric corrections), which was tailored mainly to the AISA Eagle instrument operated at CzechGlobe since 2004, has been now modified to fit the new system and users needs. Continuous development of the processing chain is now focused mainly on establishing pre-processing of thermal data including emissivity estimation and also on joint processing of hyperspectral and laser scanning data.

scholarly journals Hyper-spectral imaging system with harmonic diffraction element in medium and far infrared

2010 ◽  
Vol 59 (10) ◽  
pp. 6980
Author(s):  
Liu Ying ◽  
Sun Qiang ◽  
Lu Zhen-Wu ◽  
Qu Feng ◽  
Wu Hong-Sheng ◽  
...  
Keyword(s):  
Imaging System ◽  
Spectral Imaging ◽  
Far Infrared ◽  
Hyper Spectral ◽  
Hyper Spectral Imaging

scholarly journals Study on Hyper Spectral Imaging

2021 ◽  
Vol 9 (VI) ◽  
pp. 2017-2021
Author(s):  
Bathula Namratha
Keyword(s):  
Data Acquisition ◽  
Situation Awareness ◽  
Spectral Imaging ◽  
Image Resolution ◽  
Imaging Data ◽  
Spectral Signatures ◽  
Spectral Bands ◽  
Hyper Spectral ◽  
Hyper Spectral Imaging ◽  
Imaging Sensors

Spectroscopy deals with how light behave in the target and recognize materials bases on their different spectral signatures. Spectrum describes the amount and range of radiation that is emitted, reflected or transmitted from the target. Hyper spectral data acquisition and exploitation by providing imaging sensors and software solutions covering hundreds of spectral bands from UV-VIS to SWIS is used to observe Earth, atmospheric science, space situation awareness etc. The work focuses primarily on hyper spectral imaging, data acquisition methods, Image resolution improvement strategies.

IRIS: a novel spectral imaging system for the analysis of cultural heritage objects

2011 ◽  
Author(s):  
V. M. Papadakis ◽  
Y. Orphanos ◽  
S. Kogou ◽  
K. Melessanaki ◽  
P. Pouli ◽  
...  
Keyword(s):  
Cultural Heritage ◽  
Imaging System ◽  
Spectral Imaging ◽  
Cultural Heritage Objects

An advanced scanning method for space-borne hyper-spectral imaging system

2011 ◽  
Author(s):  
Yue-ming Wang ◽  
Jun-Wei Lang ◽  
Jian-Yu Wang ◽  
Zi-Qing Jiang
Keyword(s):  
Imaging System ◽  
Spectral Imaging ◽  
Scanning Method ◽  
Hyper Spectral ◽  
Hyper Spectral Imaging

scholarly journals Automatic Ink Mismatch Detection in Hyperspectral Images Using Kmeans Clustering.pdf

2020 ◽  
Author(s):  
Muhammad Talha ◽  
Noman Raza Shah ◽  
Fizza Imtiaz ◽  
Aneeqah Azmat
Keyword(s):  
Euclidean Distance ◽  
Imaging Techniques ◽  
Spectral Imaging ◽  
Physical Contact ◽  
Hyperspectral Images ◽  
Clustering Problem ◽  
Mismatch Detection ◽  
Hyper Spectral ◽  
Hyper Spectral Imaging

Hyper spectral imaging (HSI) is a technique that is used to obtain the spectrum for each pixel in the image. It helps in finding objects and identifying materials etc. Such an identification is very difficult using other imaging techniques. It allows the researchers to investigate the documents without any physical contact. Nowadays detection of unequal Ink mismatch based on HSI has shown vast improvement in distinguishing the inks. Detection of unequal Ink mismatch is an unbalanced clustering problem. This paper used K-means Clustering for ink mismatch detection. K-means Clustering find same subgroups in the data based on Euclidean distance. This paper demonstrates performance in unequal Ink mismatch based on HSI.

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