Submit to Sensors Review for Sensors Propose a Special Issue

Journal Browser

► Journal Browser

Sensors for Imaging Cultural Heritage: Technologies, Methods and Data Processing

Special Issue Editors
Special Issue Information
Keywords
Published Papers

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".

Deadline for manuscript submissions: closed (25 March 2023) | Viewed by 31029

Share This Special Issue

Special Issue Editors

Dr. Marcello Picollo

E-Mail Website
Guest Editor

Istituto di Fisica Applicata “Nello Carrara” del Consiglio Nazionale delle Ricerche (IFAC-CNR), Via Madonna del piano, 10, 50019 Sesto Fiorentino, FI, Italy
Interests: materials art; materials science; spectroscopy; infrared spectroscopy; heritage; sensors
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Eva M. Valero Benito

E-Mail Website
Guest Editor

Department of Optics, University of Granada, 18071 Granada, Spain
Interests: multispectral and hyperspectral imaging; color image processing; saliency prediction; spectral imaging of artwork
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Kirk Martinez

E-Mail Website
Guest Editor

Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, UK
Interests: Internet of Things; environmental sensor networks; imaging
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Imaging continues to bring new ways to investigate our cultural heritage (CH). Innovations in various types of imaging sensors, optics, acquisition methods, and data processing allow clearer, deeper, and consequently new views of objects that can be obtained faster than previously. This special issue will focus on the techniques that go beyond a single digital camera image and aim to support documentation and conservation of CH objects. This Special Issue discusses imaging spectroscopy, multimodal imaging, and computational imaging, as well as includes descriptions of the best methodologies and acquisition parameters of workflows for operating imaging devices under indoor and outdoor environments. Topics dealing with contribution defining, testing, implementing, and developing specific criteria for optimizing the imaging systems, the methodologies, and the format of acquired data as well as the processing procedures for analysis, storage, usage, and dissemination of imaging data and results on 2D and 3D CH objects are also welcome.

Topics

Raman Imaging spectroscopy
Hyperspectral imaging
Reflectance Transformation Imaging
2D and 3D image processing pipelines for data extraction
Image registration for cultural heritage applications
Pigment identification
Imaging acquisition technical setup
Endmember extraction and unmixing algorithms
Deep learning applied to cultural heritage

Dr. Marcello Picollo

Prof. Dr. Eva M. Valero Benito

Prof. Dr. Kirk Martinez
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

imaging spectroscopy
image processing
state-of-the-art capture devices
challenges in experimental design and methodology
multimodal imaging
image standardization

Published Papers (12 papers)

Download All Papers

Research

Jump to: Review

14 pages, 16264 KiB

Open AccessArticle

A Novel Transmittance Vis–NIR Hyper-Spectral Imaging Scanner for Analysis of Photographic Negatives: A Potential Tool for Photography Conservation

by Costanza Cucci, Andrea Casini, Lorenzo Stefani, Barbara Cattaneo and Marcello Picollo

Sensors 2023, 23(7), 3562; https://doi.org/10.3390/s23073562 - 29 Mar 2023

Cited by 1 | Viewed by 1553

Abstract

This work illustrates a novel prototype of a transmittance hyperspectral imaging (HSI) scanner, operating in the 400–900 nm range, and designed on purpose for non-invasive analysis of photographic materials, such as negatives, films and slides. The instrument provides high-quality spectral data and high-definition spectral images on targets of small size (e.g., 35 mm film strips) and is the first example of HSI instrumentation specifically designed for applications in the photographic conservation field. The instrument was tested in laboratory and on a set of specimens selected from a damaged photographic archive. This experimentation, though preliminary, demonstrated the soundness of a technical approach based on HSI for large-scale spectroscopic characterization of photographic archival materials. The obtained results encourage the continuation of experimentation of HSI as an advanced tool for photography conservation. Full article

(This article belongs to the Special Issue Sensors for Imaging Cultural Heritage: Technologies, Methods and Data Processing)

► Show Figures

Figure 1

21 pages, 10891 KiB

Open AccessArticle

Multiband Photogrammetry and Hybrid Image Analysis for the Investigation of a Wall Painting by Paolo de San Leocadio and Francesco Pagano in the Cathedral of Valencia

by Max Rahrig, Miguel Ángel Herrero Cortell and José Luis Lerma

Sensors 2023, 23(4), 2301; https://doi.org/10.3390/s23042301 - 18 Feb 2023

Cited by 3 | Viewed by 1966

Abstract

A workflow for the photogrammetric combination of non-invasive multispectral imaging techniques ranging from ultraviolet (UV) and visible (VIS) to near infrared (NIR) for the investigation of wall paintings is presented. Hereby, different methods for image analysis and visualisation techniques are discussed. This includes the combination of spectral bands in hybrid false-colour images and image analysis by applying NDVI/NDPI and PCA. The aim of the research is to generate a high-resolution photogrammetric image set, providing information on underdrawings, material differences, damages, painting techniques and conservation measures. The image data are superimposed with pixel accuracy in a geographic information system (GIS) for further analysis, tracing of observations and findings and the annotation of further information. The research is carried out on the ‘Adoration of the Shepherds’, an early Spanish Renaissance wall painting created in 1472 by Paolo de San Leocadio and Francesco Pagano in the Cathedral of Valencia. The wall painting is preserved in an unfinished condition, and half of it is represented by the initial plaster and preparation layers. This gives the possibility to compare and evaluate the observations of the finished areas as well as carry out an in-depth study of the working techniques. Full article

(This article belongs to the Special Issue Sensors for Imaging Cultural Heritage: Technologies, Methods and Data Processing)

► Show Figures

Figure 1

19 pages, 38957 KiB

Open AccessArticle

Enhancement and Restoration of Scratched Murals Based on Hyperspectral Imaging—A Case Study of Murals in the Baoguang Hall of Qutan Temple, Qinghai, China

by Pengyu Sun, Miaole Hou, Shuqiang Lyu, Wanfu Wang, Shuyang Li, Jincheng Mao and Songnian Li

Sensors 2022, 22(24), 9780; https://doi.org/10.3390/s22249780 - 13 Dec 2022

Cited by 3 | Viewed by 1895

Abstract

Environmental changes and human activities have caused serious degradation of murals around the world. Scratches are one of the most common issues in these damaged murals. We propose a new method for virtually enhancing and removing scratches from murals; which can provide an auxiliary reference and support for actual restoration. First, principal component analysis (PCA) was performed on the hyperspectral data of a mural after reflectance correction, and high-pass filtering was performed on the selected first principal component image. Principal component fusion was used to replace the original first principal component with a high-pass filtered first principal component image, which was then inverse PCA transformed with the other original principal component images to obtain an enhanced hyperspectral image. The linear information in the mural was therefore enhanced, and the differences between the scratches and background improved. Second, the enhanced hyperspectral image of the mural was synthesized as a true colour image and converted to the HSV colour space. The light brightness component of the image was estimated using the multi-scale Gaussian function and corrected with a 2D gamma function, thus solving the problem of localised darkness in the murals. Finally, the enhanced mural images were applied as input to the triplet domain translation network pretrained model. The local branches in the translation network perform overall noise smoothing and colour recovery of the mural, while the partial nonlocal block is used to extract the information from the scratches. The mapping process was learned in the hidden space for virtual removal of the scratches. In addition, we added a Butterworth high-pass filter at the end of the network to generate the final restoration result of the mural with a clearer visual effect and richer high-frequency information. We verified and validated these methods for murals in the Baoguang Hall of Qutan Temple. The results show that the proposed method outperforms the restoration results of the total variation (TV) model, curvature-driven diffusion (CDD) model, and Criminisi algorithm. Moreover, the proposed combined method produces better recovery results and improves the visual richness, readability, and artistic expression of the murals compared with direct recovery using a triple domain translation network. Full article

(This article belongs to the Special Issue Sensors for Imaging Cultural Heritage: Technologies, Methods and Data Processing)

► Show Figures

Figure 1

16 pages, 5057 KiB

Open AccessArticle

High-Definition Survey of Architectural Heritage Fusing Multisensors—The Case of Beamless Hall at Linggu Temple in Nanjing, China

by Junwei Fang, Yingying Zhang, Yiru Zhang, Huayu Guo and Zheng Sun

Sensors 2022, 22(9), 3369; https://doi.org/10.3390/s22093369 - 28 Apr 2022

Cited by 6 | Viewed by 2003

Abstract

Following the development of digital measurement technology in recent years, the information contained in the measurement outcomes have become increasingly rich. However, the traditional graphical representation method based on vector graph needs to be updated. In this study, we use the Beamless Hall of Linggu Temple as an example. Measurements are conducted by using digital techniques, including three-dimensional (3D) laser scanning, close-range photogrammetry, and infrared thermal imaging. The pseudocolours that express spatial information and moisture distribution are calculated and generated through point clouds, which are used to express the land subsidence, wall deformation, moisture distribution, and other effects of the Beamless Hall. Furthermore, combining it with two-dimensional (2D) graphical representation, such as the plan, elevation, and section, damage-related information can be expressed intuitively and efficiently. This method can combine the advantages of graphics and images to provide a comprehensive and intuitive representation of the digital measurement results of brick architecture heritage. It can also provide a reference for surveying similar monuments and buildings of our architectural heritage. Full article

(This article belongs to the Special Issue Sensors for Imaging Cultural Heritage: Technologies, Methods and Data Processing)

► Show Figures

Figure 1

19 pages, 11083 KiB

Open AccessArticle

Application of Factorisation Methods to Analysis of Elemental Distribution Maps Acquired with a Full-Field XRF Imaging Spectrometer

by Bartłomiej Łach, Tomasz Fiutowski, Stefan Koperny, Paulina Krupska-Wolas, Marek Lankosz, Agata Mendys-Frodyma, Bartosz Mindur, Krzysztof Świentek, Piotr Wiącek, Paweł M. Wróbel and Władysław Dąbrowski

Sensors 2021, 21(23), 7965; https://doi.org/10.3390/s21237965 - 29 Nov 2021

Cited by 3 | Viewed by 1635

Abstract

The goal of the work was to investigate the possible application of factor analysis methods for processing X-ray Fluorescence (XRF) data acquired with a full-field XRF spectrometer employing a position-sensitive and energy-dispersive Gas Electron Multiplier (GEM) detector, which provides only limited energy resolution at a level of 18% Full Width at Half Maximum (FWHM) at 5.9 keV. In this article, we present the design and performance of the full-field imaging spectrometer and the results of case studies performed using the developed instrument. The XRF imaging data collected for two historical paintings are presented along with the procedures applied to data calibration and analysis. The maps of elemental distributions were built using three different analysis methods: Region of Interest (ROI), Non-Negative Matrix Factorisation (NMF), and Principal Component Analysis (PCA). The results obtained for these paintings show that the factor analysis methods NMF and PCA provide significant enhancement of selectivity of the elemental analysis in case of limited energy resolution of the spectrometer. Full article

(This article belongs to the Special Issue Sensors for Imaging Cultural Heritage: Technologies, Methods and Data Processing)

► Show Figures

Figure 1

26 pages, 73156 KiB

Open AccessArticle

Segmentation of Change in Surface Geometry Analysis for Cultural Heritage Applications

by Sunita Saha, Jacek Martusewicz, Noëlle L. W. Streeton and Robert Sitnik

Sensors 2021, 21(14), 4899; https://doi.org/10.3390/s21144899 - 19 Jul 2021

Cited by 8 | Viewed by 2440

Abstract

This work proposes a change-based segmentation method for applications to cultural heritage (CH) imaging to perform monitoring and assess changes at each surface point. It can be used as a support or component of the 3D sensors to analyze surface geometry changes. In this research, we proposed a new method to identify surface changes employing segmentation based on 3D geometrical data acquired at different time intervals. The geometrical comparison was performed by calculating point-to-point Euclidean distances for each pair of surface points between the target and source geometry models. Four other methods for local distance measurement were proposed and tested. In the segmentation method, we analyze the local histograms of the distances between the measuring points of the source and target models. Then the parameters of these histograms are determined, and predefined classes are assigned to target surface points. The proposed methodology was evaluated by considering two different case studies of restoration issues on CH surfaces and monitoring them over time. The results were presented with a colormap visualization for each category of the detected change in the analysis. The proposed segmentation method will help in the field of conservation and restoration for the documentation and quantification of geometrical surface change information. This analysis can help in decision-making for the assessment of damage and potential prevention of further damage, and the interpretation of measurement results. Full article

(This article belongs to the Special Issue Sensors for Imaging Cultural Heritage: Technologies, Methods and Data Processing)

► Show Figures

Figure 1

16 pages, 12134 KiB

Open AccessCommunication

3-D Multi-Component Reverse Time Migration Method for Tunnel Seismic Data

by Peng Guan, Cuifa Shao, Yuyong Jiao, Guohua Zhang, Bin Li, Jie Zhou and Pei Huang

Sensors 2021, 21(9), 3244; https://doi.org/10.3390/s21093244 - 07 May 2021

Cited by 3 | Viewed by 1871

Abstract

Migration imaging is a key step in tunnel seismic data processing. Due to the limitation of tunnel space, tunnel seismic data are small-quantity, multi-component, and have a small offset. Kirchhoff migration based on the ray theory is limited to the migration aperture and has low migration imaging accuracy. Kirchhoff migration can no longer meet the requirements of high-precision migration imaging. The reverse time migration (RTM) method is used to realize cross-correlation imaging by reverse-time recursion principle of the wave equation. The 3-D RTM method cannot only overcome the effect of small offset, but also realize multi-component data imaging, which is the most accurate migration method for tunnel seismic data. In this paper, we will study the 3-D RTM method for multi-component tunnel seismic data. Combined with the modeled data and the measured data, the imaging accuracy of the 3-D Kirchhoff migration and 3-D RTM is analyzed in detail. By comparing single-component and multi-component Kirchhoff migration and RTM profile, the advantages of the multi-component RTM method are summarized. Compared with the Kirchhoff migration method, the 3-D RTM method has the following advantages: (1) it can overcome the effect of small offset and expand the range of migration imaging; (2) multi-component data can be realized to improve the energy of anomalous interface; (3) it can make full use of multiple waves to realize migration imaging and improve the resolution of the anomalous interface. The modeled data and the measured data prove the advantages of the 3-D multi-component RTM method. Full article

(This article belongs to the Special Issue Sensors for Imaging Cultural Heritage: Technologies, Methods and Data Processing)

► Show Figures

Figure 1

16 pages, 3889 KiB

Open AccessArticle

Comparison of Imaging Models for Spectral Unmixing in Oil Painting

by Federico Grillini, Jean-Baptiste Thomas and Sony George

Sensors 2021, 21(7), 2471; https://doi.org/10.3390/s21072471 - 02 Apr 2021

Cited by 15 | Viewed by 2684

Abstract

The radiation captured in spectral imaging depends on both the complex light–matter interaction and the integration of the radiant light by the imaging system. In order to obtain material-specific information, it is important to define and invert an imaging process that takes into account both aspects. In this article, we investigate the use of several mixing models and evaluate their performances in the study of oil paintings. We propose an evaluation protocol, based on different features, i.e., spectral reconstruction, pigment mapping, and concentration estimation, which allows investigating the different properties of those mixing models in the context of spectral imaging. We conduct our experiment on oil-painted mockup samples of mixtures and show that models based on subtractive mixing perform the best for those materials. Full article

(This article belongs to the Special Issue Sensors for Imaging Cultural Heritage: Technologies, Methods and Data Processing)

► Show Figures

Figure 1

17 pages, 4185 KiB

Open AccessArticle

Evaluation of Cleaning Processes Using Colorimetric and Spectral Data for the Removal of Layers of Limewash from Medieval Plasterwork

by Miguel Ángel Martínez-Domingo, Ana Isabel Calero Castillo, Eva Vivar García and Eva M. Valero

Sensors 2020, 20(24), 7147; https://doi.org/10.3390/s20247147 - 13 Dec 2020

Cited by 10 | Viewed by 2161

Abstract

In the cultural heritage preservation of medieval buildings, it is common to find plaster walls covered in lime, which previously were painted in polychromy. The conservation interventions usually try to remove the whitewash, whilst maintaining the original color of the painted wall as much as possible. However, there is no agreement on which cleaning technique best preserves the original appearance of the colored plaster. Different pigments found below the lime layer may behave differently depending on the cleaning technique used. Usually, colorimetric or photometric area-based measurements are carried out to study the color of the cleaned areas to compare with their original color, obtained from pre-made plaster probes. However, this methodology fails when the mean color difference is not enough to fully characterize the changes in texture and color appearance. This study presents a set of experiments carried out using two different pigments (cinnabar and malachite) covered with lime, and treated with nine different cleaning techniques on plaster probes prepared according to medieval techniques. We have studied the effect of the cleaning process on the color and the homogeneity of the samples using a hyperspectral imaging workflow. Four different analysis methods are presented and discussed. Our results show that the proposed analysis is able to provide a much more comprehensive and diversified characterization of the quality of the cleaning method compared to the commonly used colorimetric or photometric area-based measurements. Full article

(This article belongs to the Special Issue Sensors for Imaging Cultural Heritage: Technologies, Methods and Data Processing)

► Show Figures

Figure 1

26 pages, 22557 KiB

Open AccessEditor’s ChoiceArticle

The Use of Low-Cost Unmanned Aerial Vehicles in the Process of Building Models for Cultural Tourism, 3D Web and Augmented/Mixed Reality Applications

by Tomasz Templin and Dariusz Popielarczyk

Sensors 2020, 20(19), 5457; https://doi.org/10.3390/s20195457 - 23 Sep 2020

Cited by 34 | Viewed by 5200

Abstract

Unmanned Aerial Systems (UAS) are widely used in low-cost photogrammetry. Even small Unmanned Aerial Vehicles (UAV) can deliver valuable data for the inventory of inaccessible and dangerous areas or objects. The acquisition of data for 3D object modeling is a complicated, time-consuming, and cost-intensive process. It requires the use of expensive equipment and often manual work as well as professional software. These are major barriers limiting the development of modern tourist platforms that promote local attractions. Information technologies offer new opportunities for the development of the services market, including the development of smart tourism services, as an integral part of the smart city concept. 3D models are an important element of this process as they form the basis for the use of new visualization technologies, such as Virtual, Mixed, and Augmented Reality (VR/MR/AR). 3D modeling provides a new opportunity to use AR/MR technology to present information about objects, virtual tours of the historic buildings, and their promotion. It also creates an opportunity to preserve the architectural heritage and preventive maintenance of buildings. Despite the increasing use of new measuring platforms and computer modeling techniques, the implementation of 3D building models in smart tourism services is still limited, focusing more on the results of scientific projects rather than on the implementation of the new ones. The paper presents an universal methodology for the inventory of historical buildings using low-cost UAVs. It describes the most important aspects related to the process of planning UAV measurement missions and photogrammetric data acquisition. The construction of 3D models and the possibilities of their further use to build smart tourism services based on Web/AR/MR/VR technology was also presented. Full article

(This article belongs to the Special Issue Sensors for Imaging Cultural Heritage: Technologies, Methods and Data Processing)

► Show Figures

Figure 1

21 pages, 3759 KiB

Open AccessArticle

Assessment of Cracking Widths in a Concrete Wall Based on TIR Radiances of Cracking

by Tung-Ching Su

Sensors 2020, 20(17), 4980; https://doi.org/10.3390/s20174980 - 02 Sep 2020

Cited by 14 | Viewed by 3080

Abstract

The techniques of concrete crack detection, as well as assessments based on thermography coupled with ultrasound, have been presented in many works; however, they have generally needed an additional source of thermal infrared (TIR) radiance and have only been applied in laboratories. Considering the accessibility of thermal infrared cameras, a TIR camera (NEC F30W) was employed to detect cracking in the concrete wall of an historic house with a western architectural style in Kinmen, Taiwan, based on the TIR radiances of cracking. An operation procedure involving a series of image processing and statistical analysis processes was designed to evaluate the performance of the TIR camera in the assessment of the cracking width. This procedure using multiple measurements was implemented from March to August 2019, and the t-tests indicated that the temperature differences between the inside and outline of the concrete cracks remained insignificant as the temperature or relative humidity (RH) in the subtropical climate rose. The experimental results of the operation procedure indicated that the maximum focusing range, which is related to the size of the sensor array, and the minimum detectable crack width of a TIR camera should be 1.0 m and 6.0 mm, respectively, in order to derive a linear regression model with a determination coefficient R² of 0.733 to estimate the cracking widths, based on the temperature gradients. The validation results showed that there was an approximate R² value of 0.8 and a total root mean square error of ±2.5 mm between the cracking width estimations and the observations. Full article

(This article belongs to the Special Issue Sensors for Imaging Cultural Heritage: Technologies, Methods and Data Processing)

► Show Figures

Figure 1

Review

Jump to: Research

25 pages, 2181 KiB

Open AccessReview

Neural Networks for Hyperspectral Imaging of Historical Paintings: A Practical Review

by Lingxi Liu, Tsveta Miteva, Giovanni Delnevo, Silvia Mirri, Philippe Walter, Laurence de Viguerie and Emeline Pouyet

Sensors 2023, 23(5), 2419; https://doi.org/10.3390/s23052419 - 22 Feb 2023

Cited by 4 | Viewed by 2716

Abstract

Hyperspectral imaging (HSI) has become widely used in cultural heritage (CH). This very efficient method for artwork analysis is connected with the generation of large amounts of spectral data. The effective processing of such heavy spectral datasets remains an active research area. Along with the firmly established statistical and multivariate analysis methods, neural networks (NNs) represent a promising alternative in the field of CH. Over the last five years, the application of NNs for pigment identification and classification based on HSI datasets has drastically expanded due to the flexibility of the types of data they can process, and their superior ability to extract structures contained in the raw spectral data. This review provides an exhaustive analysis of the literature related to NNs applied for HSI data in the CH field. We outline the existing data processing workflows and propose a comprehensive comparison of the applications and limitations of the various input dataset preparation methods and NN architectures. By leveraging NN strategies in CH, the paper contributes to a wider and more systematic application of this novel data analysis method. Full article

(This article belongs to the Special Issue Sensors for Imaging Cultural Heritage: Technologies, Methods and Data Processing)

► Show Figures