Automatic registration and mosaicking of technical images of Old Master paintings

Conover, Damon M.; Delaney, John K.; Loew, Murray H.

doi:10.1007/s00339-015-9140-1

Cited by 59 publications

(44 citation statements)

References 17 publications

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“…Image processing and analysis of the VNIR and SWIR image cubes began with flat fielding using a dark image cube and an image cube of a Spectralon (Labsphere, NH) white panel to correct for the dark offset and non-uniform illumination of the painting, as well as to convert to apparent reflectance. The resulting calibrated image cubes were then mosaicked and spatially registered to a high-resolution color image using a previously described algorithm written in Matlab (2012b, MathWorks, MA) [29]. Small black and white spectralon in-scene standards were used to further improve the calibration using the empirical line calibration routine in ENVI (Exelis, USA).…”

Section: Reflectance Imaging Spectroscopy (Ris)mentioning

confidence: 99%

Separating two painting campaigns in Saul and David, attributed to Rembrandt, using macroscale reflectance and XRF imaging spectroscopies and microscale paint analysis

et al. 2018

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Late paintings of Rembrandt van Rijn (1606-1669) offer intriguing problems for both art historians and conservation scientists. In the research presented here, the key question addressed is whether observed stylistic differences in paint handling can be correlated with material differences. In Saul and David, in the collection of the Royal Picture Gallery Mauritshuis in The Hague, NL, the stylistic differences between the loose brushwork of Saul's cloak and the more detailed depiction of his turban and the figure of David have been associated with at least two painting stages since the late 1960s, but the attribution of each stage has been debated in the art historical literature. Stylistic evaluation of the paint handling in the two stages, based on magnified surface examination, is further described here. One of the research goals was to determine whether the stylistic differences could be further differentiated with macroscale and microscale methods of material analysis. To address this, selected areas of the painting having pronounced stylistic differences were investigated with two macroscopic chemical imaging methods, X-ray fluorescence and reflectance imaging spectroscopies. The pigments used were identified and their spatial distribution was mapped. The mapping results show that the passages rendered in more detail and associated stylistically with the first painting stage, such as the orange-red color of David's garment or the Greek key design in Saul's turban, were painted with predominately red ochre mixed with vermilion. The regions of loose, bold brushwork, such as the orange-red slashing strokes in the interior of Saul's cloak, associated with the second painting stage, were painted with predominately red ochre without vermilion. These macroscale imaging results were confirmed and extended with scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX) analysis of three cross-sections taken from regions of stylistic differences associated with the two painting stages, including one sample each from the right and left sleeve of David, and one from the interior of Saul's cloak. SEM-EDX also identified a trace component, barium sulfate, associated with the red ochre of the second stage revisions. Combining mapping information from two spectroscopic imaging methods with localized information from microscopic samples has clearly shown that the stylistic differences observed in the paint handling are affiliated with differences in the chemical composition of the paints.

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Section: Reflectance Imaging Spectroscopy (Ris)mentioning

confidence: 99%

Separating two painting campaigns in Saul and David, attributed to Rembrandt, using macroscale reflectance and XRF imaging spectroscopies and microscale paint analysis

et al. 2018

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“…The analysis was performed using a Matlab script (sfrmat.m, Burns Digital Imaging, LLC). The mosaicking and registration of the IRR images were done using scripts written in Matlab and described in Conover et al [12]. The principal component analysis was done using the Minimum Noise Fraction in ENVI (Harris Geospatial Solutions, CO).…”

Section: Methodsmentioning

confidence: 99%

“…These digital images were arranged in layers (z-stack) and processed with an automatic processing tool that merged the stack in a single image, locally selecting the content from the sharpest layer. The resulting sharp image frames were then mosaicked with a point-based registration algorithm [12] to form a sharp high-resolution infrared reflectogram of the whole painting (Fig. 7).…”

Section: Imaging Warped Un-cradled Panel Paintingsmentioning

confidence: 99%

“…This has created interest in improved stitching software (both manual and semi-automatic routines). Fortunately, advances in computer processing power and new mosaicking software [12] have made mosaicking and registration less daunting. One useful advantage of the small field of view of the translating step and stare camera system compared to all but the single pixel scanners, is that the final IRR images produced are closer to orthophoto images.…”

Section: Introductionmentioning

confidence: 99%

“…To ensure the system could be used to examine works on paper and parchment, increased light sensitivity was deemed necessary as well. The resulting camera system thus took advantage of the availability of high quality, near-infrared lenses optimized for the 1000-2500 nm spectral region and newly developed image registration software tools specifically developed for mosaicking and registering IRR image frames [12]. The resulting sensor system can be used with both simple wooden easels and computer-controlled easels that provide automatic step and stare collections.…”

Section: Introductionmentioning

confidence: 99%

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A high sensitivity, low noise and high spatial resolution multi-band infrared reflectography camera for the study of paintings and works on paper

et al. 2017

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Background: Infrared reflectography (IRR) remains an important method to visualize underdrawing and compositional changes in paintings. Older IRR camera systems are being replaced with near-infrared cameras consisting of room temperature infrared detector arrays made out of indium gallium arsenide (InGaAs) that operate over the spectral range of ~900 to 1700 nm. Two camera types are becoming prevalent. The first is staring array infrared cameras having 0.25-1 Megapixels where the camera or painting is moved to acquire tens of individual images that are later mosaicked together to create the infrared reflectogram. The second camera type is scanning back cameras in which a small InGaAs array (linear or area array) is mechanically scanned over a large image formed by the camera lens to create the reflectogram, typically 16 Megapixels. Both systems have advantages and disadvantages. The staring IR array cameras offer more flexible collection formats, provide live images, and allow for the use of spectral bandpass filters that can provide reflectograms with better contrast in some cases. They do require a mechanical system for moving the camera or the artwork and post-capture image mosaicking. Scanning back cameras eliminate or reduce the amount of mosaicking and movement of the camera, however the need to minimize light exposure to the artwork requires short integration times, and thus limits the use of spectral bandpass filters. In general, InGaAs cameras are not sensitive in the 1700 to ~2300 nm spectral region, which has been identified in prior studies as useful for examining paintings with copper green pigments or thick lead white paints. Prior studies using cameras with sensitivity from 1000 to 2500 nm have found in general the performance at wavelengths longer than 1700 nm degraded relative to the performance at shorter wavelengths. Thus, there is interest in a camera system having improved performance out to 2500 nm that can utilize spectral bandpass filters.

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Molecular Fluorescence Imaging Spectroscopy for Mapping Low Concentrations of Red Lake Pigments: Van Gogh's PaintingThe Olive Orchard

et al. 2020

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Vincent van Gogh used fugitive red lake pigments that have faded in some paintings. Mapping their distribution is key to understanding how his paintings have changed with time. While red lake pigments can be identified from microsamples, in situ identification and mapping remain challenging. This paper explores the ability of molecular fluorescence imaging spectroscopy to identify and, more importantly, map residual non‐degraded red lakes. The high sensitivity of this method enabled identification of the emission spectra of eosin (tetrabromine fluorescein) lake mixed with lead or zinc white at lower concentrations than elemental X‐ray fluorescence (XRF) spectroscopy used on account of bromine. The molecular fluorescence mapping of residual eosin and two carmine red lakes in van Gogh's The Olive Orchard is demonstrated and compared with XRF imaging spectroscopy. The red lakes are consistent with the composition of paint tubes known to have been used by van Gogh.

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Automatic registration and mosaicking of technical images of Old Master paintings

Cited by 59 publications

References 17 publications

Separating two painting campaigns in Saul and David, attributed to Rembrandt, using macroscale reflectance and XRF imaging spectroscopies and microscale paint analysis

Separating two painting campaigns in Saul and David, attributed to Rembrandt, using macroscale reflectance and XRF imaging spectroscopies and microscale paint analysis

A high sensitivity, low noise and high spatial resolution multi-band infrared reflectography camera for the study of paintings and works on paper

Molecular Fluorescence Imaging Spectroscopy for Mapping Low Concentrations of Red Lake Pigments: Van Gogh's PaintingThe Olive Orchard

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