Yusuke Murayama

Analytical Imaging of Traditional Japanese Paintings Using Multispectral Images

In this study, the influence of lighting conditions on the reconstruction of spectral reflectance and image stitching was explored. Pigment estimation using the reconstructed spectral reflectance was also discussed. Spectral reflectance was estimated using pseudoinverse model from multispectral images of a traditional Japanese painting. It was observed that the accuracy of the estimation is greatly influenced by lighting conditions. High specular reflection on the target yielded large amount of estimation errors. On the other hand, it was observed that in addition to specular reflection, the distribution of light highly affects image stitching. Image stitching is important especially when acquiring images of large objects. Finally, pigments used on the painting were estimated using spectral curve matching of the reconstructed spectral reflectance compared to a pigment database. It was shown that multispectral images could be used for the analytical imaging of artworks.

Pigment identification based on spectral reflectance reconstructed from RGB images for cultural heritage investigations

Common analysis techniques for artworks, such as X-ray based techniques, usually employ high-energy radiation sources. It also oftentimes requires the removal of material from the sample making the analysis relatively destructive. This is unacceptable for samples with high cultural value. Therefore, there is a need to develop alternative nondestructive and noninvasive analysis methods. This paper presents an approach for pigment estimation of Japanese paintings. Reflectance spectra were reconstructed from the RGB values of digital images with the help of multiple linear regression analysis. A reference database with the measured reflectance spectra of the most common pigments used in Japanese artworks was developed and used for identification by comparison and matching. Results have shown that estimation can be successfully performed with only 2% error. The estimation results show some promise that the system could become a powerful tool for the analysis of cultural heritage.

A line scan camera based stereo method for high resolution 3D image reconstruction

A Line-scan camera based stereo method for high resolution 3D image reconstruction is proposed. The imaging model of a line scan camera is addressed in detail to describe the relationship between the coordinate of a physical object in space and the coordinate of its image captured by the scanner. Affine-SIFT feature detector is utilized for establishing dense stereo correspondence. Experimental result demonstrates the effectiveness and merit of this method to high resolution digitization of cultural heritages.

Non-destructive analytical imaging of metallic surfaces using spectral measurements and ultrahigh-resolution scanning for cultural heritage investigation

This paper presents a new approach for analyzing spectroscopic characteristic of metallic surfaces using spectroscopic and image analysis. This method is useful for contactless and non destructive analysis of cultural heritage. Spectral luminance, CIELAB, and CIEXYZ value of more than 80 metallic surfaces were measured with spectrometer and scanned to examine spectroscopic characteristics of foils by using multiband images. This analysis through imaging can improve the method for extracting difference related to types of metallic foils. Firstly, the spectral reflectance of each foil was measured ranging from 220 to 850 nm in steps of 1 nm. The images were captured with color and monochromatic camera using color filter in order to analyze the targets by multispectral approach. Then, principal component analysis (PCA) was conducted with image pixel value of each target. The results have shown that the spectral reflectance whose peak and change rate at a particular wavelength region differed from each foils, and that the multispectral images extracted the difference in spectral characteristics related to different types of metallic foils and Japanese papers. This could be useful in distinguishing among foils. This provides some promise that unknown metallic foils can be identified through the measurement of their spectroscopic features.

Polarized light scanning for cultural heritage investigation

Numerous cultural heritage art works have shiny surfaces resulting form gold, silver, and other metallic pigments. In addition varnish overlayer on oil paintings makes it challenging to retrieve true color information. This is due to the great effect of lighting condition when images are acquired and viewed. The reflection of light from such surfaces is a combination of the surfaces specular and diffused light reflections. In this paper, this specific problems encountered when digitizing cultural heritage were discussed. Experimental results using the images acquired with a high-resolution large flat bed scanner, together with a mathematical method for processing the captured images were presented and discussed in detail. Focus was given in separating the diffused and specular components of the reflected light for the purpose of analytical imaging. The mathematical algorithm developed in this study enables imaging of cultural heritage with shiny and glossy surfaces effectively and efficiently.

Bayesian image superresolution for hyperspectral image reconstruction

This study presents a novel method which applies superresolution to hyperspectral image reconstruction in order to achieve a more efficient spectral imaging method. Theories of spectral reflectance estimation, such as Wiener estimation, have reduced the time and problems faced in spectral imaging. Recently Wiener estimation has been extended to increase not only the spectral resolution but also the spatial resolution of a hyperspectral image by combining the methods for image deblurring. However, there is a demand for more efficient spectral imaging techniques. This study extended the Wiener estimation further to achieve superresolution beyond simple deblurring because superresolution has more advantages: the possibility of getting higher spatial resolution, and the automatic registration of multispectral images. Maximization of the marginal likelihood function is employed in this method to reconstruct the high resolution hyperspectral image on the basis of Bayesian image superresolution. The obvious effect of superresolution was validated through an experiment using acquired multispectral images of a Japanese traditional painting.

Application of Bayesian image superresolution to spectral reflectance estimation

Abstract. Hyperspectral imaging provides us with high-dimensional, scene-independent color information but faces problems such as long image acquisition time and severe lighting and focusing conditions. To achieve efficient spectral imaging, this study presents an extended method of Bayesian image superresolution. The proposed method increases both the spatial and the wavelength resolution of input images and enables the processing of hyperspectral images to a higher resolution from easily acquired low-spatial-resolution multispectral images. In an experiment using acquired multispectral images of a Japanese traditional painting, visible and near-infrared hyperspectral images were produced, and the obvious effect of superresolution was validated.

Metamer density estimation using an identical ellipsoidal Gaussian mixture prior

We proposed an improved method for camera metamer density estimation. Camera metamer is a set of spectral reflectance of object surface which induce an identical RGB response of a color imaging devices such as a digital color camera and scanner. It is desirable for high fidelity color correction to calculate the set of metamers and then choose the optimal value in a standard color space. Previous methods adopted too simple models to represent the constraint of spectral reflectance. The set of metamers were over-estimated and it declined the accuracy of color correction. We modeled the constraint of spectral reflectance as an identical ellipsoidal Gaussian mixture distribution, and tested and compared the proposed model and two conventional models in a numerical experiment. It was found that the proposed model can represent accurately the underlying caved patterns within the given dataset and avoid generating inappropriate camera metamers. The accuracy of color correction was also evaluated supposing two commercial cameras and two standard illuminants. It was shown that higher accuracy color correction was achieved by adopting the proposed model.

Bayesian estimation of device spectral sensitivities and its application for improvement of color accuracy using color balancing filter

We proposed a Bayesian method for estimating the system spectral sensitivities of a color imaging device such as a scanner and a camera from an acquired color chart image. The system sensitivities are defined by the product of spectral sensitivities of camera and spectral power distribution of illuminant, and characterize color separation. In addition we proposed a scheme for predicting the optimal filter to increase color accuracy of the device based on the estimated sensitivities. The predicted filter is attached to the front of camera and modifies the system spectral sensitivities. This study aimed to improve color reproduction of the imaging device in practical way even if the spectral sensitivities of the device are unknown. The proposed method is derived by introducing the non-negativity, the smoothness and the zero boundaries of the sensitivity curves as prior information. All hyperparameters in the proposed Bayesian model can be determined automatically by the marginalized likelihood criterion. The modified system sensitivities and their color accuracy are predicted computationally. An experiment was carried out to test the performance of the proposed method for predicting the color accuracy improvement using two scanners. The average color difference was reduced from 3.07 to 2.04 and from 2.11 to 1.77 in the two scanners.

Analysis of Cultural Heritage by Accelerator Techniques and Analytical Imaging

In this paper we present the result of experimental investigation using two very important accelerator techniques: (1) synchrotron radiation XRF and XAFS; and (2) accelerator mass spectrometry and multispectral analytical imaging for the investigation of cultural heritage. We also want to introduce a complementary approach to the investigation of artworks which is noninvasive and nondestructive that can be applied in situ. Four major projects will be discussed to illustrate the potential applications of these accelerator and analytical imaging techniques: (1) investigation of Mongolian Textile (Genghis Khan and Kublai Khan Period) using XRF, AMS and electron microscopy; (2) XRF studies of pigments collected from Korean Buddhist paintings; (3) creating a database of elemental composition and spectral reflectance of more than 1000 Japanese pigments which have been used for traditional Japanese paintings; and (4) visible light‐near infrared spectroscopy and multispectral imaging of degraded malachite and azu...