Abstract

In the artwork conservation field, non contact diagnostic and imaging methods are widely used and most welcomed. In this work a new imaging tool, called Thermal Quasi-Reflectography (TQR), is proposed and demonstrated. It is based on the recording, by suitable procedures, of reflected infrared radiation in the MWIR band (3-5 μm). The technique, simple to perform, can provide very interesting results in the analysis of the painting surfaces. TQR was demonstrated in situ on two famous artworks: the Zavattari’s frescos in the Chapel of Theodelinda (Italy) and the masterpiece by Piero della Francesca “The Resurrection” (Italy).

© 2012 OSA

1. Introduction

At the very beginning of her Adventures [1], Alice put it very clearly: What is the use of a book without pictures? Perhaps many scientists are among those readers who share Alice's taste in books, but certainly the ubiquitous visual culture in science is becoming increasingly important [2]. This is particularly true in art conservation, which is at the forefront between art and science.

Optical methods represent powerful, versatile and attractive tools for artwork diagnostics; in fact, measurements are non-invasive and usually exhibit good sensitivity; furthermore, they have a full-field nature and the distinctive feature of providing results in a legible visual format. Optical techniques in artwork diagnostics can be distinguished according to the light source they used (coherent or not) and/or by the type of information they provide (surface conditions, structural defects, hidden layers, pigments identification etc.). We can identify two groups: 1) optical coherent techniques, which involve the use of laser sources and are more recent in the field of Non Destructive Testing (NDT); 2) “enhanced” visual techniques, involving broadband imaging in spectral regions other than the visible, which cannot be observed by the unaided eye and require suitable instrumentation.

The laser era in artwork diagnostics started in the 1970s, when holographic interferometry was applied to the detection of structural defects in panel paintings. Although holographic interferometry sensitivity and image quality are probably unrivalled in detecting defects such as detachments and cracks [35], its inherent shortcomings related to complexity and costs prevented a large diffusion of the technique in restoration practice and motivated the search for alternative coherent techniques. In particular, speckle techniques [6] have been applied to structural inspection of works of art. Electronic Speckle Pattern Interferometry (ESPI) gives fringes similar to conventional holography but with a lower image quality, due to a much more evident speckle noise. Despite the loss in resolution compared to holographic interferometry, ESPI enables the acquisition of real-time correlation fringes and it is most suitable in out-of-laboratory conditions [4,7]. It has proved to be very effective for monitoring in situ the artwork status over time, such as the object deformations due to microclimate or ambient variations [810].

Enhanced techniques based on the use of IR radiation offer several advantages in the field of art conservation, allowing to perform a prompt and non-invasive inspection of the artwork in situ. The whole infrared band can be divided, somewhat arbitrarily, into four subregions: near-infrared (NIR: 0.75-2.5 μm), mid wave-infrared (MWIR: 3-5 μm), long wave-infrared (LWIR: 7-14 μm) and extreme infrared (sometimes called very long wave-infrared VLWIR: 14-300 μm).

IR reflectography [11], which is based on image acquisition in the NIR region, is a major technique for art historians to reveal features underlying the pictorial layer, such as preparatory drawings and pentimenti (changes in the artwork made by the artist himself). Thanks to the capability to go through the different layers of the painting, NIR radiation enables the imaging of many underneath features and alterations, which can be detected by the different contrast according to the absorption properties of the materials.

Conventional reflectography is performed in wide-band modality, i.e. by acquiring the image in the large NIR band. Recently, the multispectral approach, consisting of acquiring the images in narrow bands, has been demonstrated to be very effective in the analysis of pictorial layers [12]. Multispectral reflectography allows a more differentiated detection of the painting features, and the non-destructive identification of pigments with different spectral signature in the NIR region [13].

In IR thermography [14], the MWIR or LWIR acquired by an IR camera correspond to the thermal radiation emitted from the surface of the examined object due to its temperature, according to the blackbody radiation theory. The observed temperature differences can indicate the presence of heterogeneous materials, sub-superficial or structural defects, such as voids underneath the paint layer that can be located because of the insulating properties of the air they contain.

In the study of genuine artworks, which have unknown complex stratigraphy and painting materials, an integrated approach based on a multi-mode use of the different imaging techniques yields a more comprehensive analysis. NIR and LWIR imagery can be combined, since each band contains unique and complementary information [15]. It has been shown that by adding a third complementary band, MWIR, even more useful results can be achieved [16].

Finally, very recent trends in the field of NDT are the application of Optical Coherent Tomography (OCT) and TeraHertz imaging, which are non contact and non-invasive and have a very high sensitivity. OCT, which typically uses IR wavelengths in the range 0.7–1.5 μm, can penetrate pictorial matter showing the structure of protective varnish and painting layers as well as revealing the drawing and its depth position [1719]. TeraHertz imaging was demonstrated in pigments identification, drawing visualization in wall paintings, and for observing hidden paint layers and stratigraphy on canvas paintings [20,21].

In this work, we propose a new NDT tool in artwork conservation based on imaging in the MWIR band. Basic principles of the method are given. The tool, which we called Thermal Quasi-Reflectography (TQR), is demonstrated by investigating in situ two very famous artworks. As a first example, TQR is applied on some frescos (artworks realized by a technique in which the pigments, dissolved in water, are applied on the wet plaster on walls) in the Chapel of Queen Theodelinda (15th century, Italy). Then TQR is applied to the masterwork “The Resurrection” by Piero della Francesca (circa 1460, Italy), defined by the English writer Aldous Huxley (1894-1963) as “the greatest painting in the world”.

2. Basic principles and experimental setup

When we began to develop TQR, our aim was to search for an imaging tool capable of a better differentiation of materials in a painted surface. Taking into account the art and practice of infrared spectroscopy [22], it seemed a natural choice looking at the IR spectral range greater than 3 μm, therefore the thermal bands MWIR and LWIR were good candidates for our goal. There exist some differences between imaging in these bands. Measurements in LWIR are usually less sensitive to ambient illumination; conversely, MWIR band exhibits lower optical diffraction and background radiation, which give a sharper imaging with a better contrast.

TQR takes the thermography basic concept in reverse: in a normal measurement by thermography, a temperature estimation is performed based on IR radiation emitted from the surface. This means that reflected IR radiation should be reduced or carefully taken into account. Many objects at room temperature are good sources of IR radiation at thermal wavelengths and, therefore, no artificial illumination source is needed.

TQR, conversely, is based on IR radiation reflected from the surface, this means that emitted IR radiation should be reduced with respect to the reflected one. This objective can be achieved in the following manner:

  • 1) Choosing a suitable IR band;
  • 2) Using a suitable artificial source;
  • 3) Avoiding or limiting temperature increases on the surface.

As it is well known, the amount of emitted radiation depends both on the surface temperature and the surface total emissivity, i.e. its ability to emit energy by radiation. For an opaque object, under the graybody assumption, emissivity is also related to the surface ability in reflecting energy: objects with low emissivity are good reflectors.

The spectral distribution of energy emitted by an object is given by the product of the Planck distribution for a given temperature with the emissivity of the object. In the vicinity of the room temperature (293 K), the Planck distribution (see Fig. 1 ) has a maximum in the LWIR (around 10 μm); the peak in the MWIR is approximately one-fourth of this maximum. In terms of total energy emitted, it can be easily shown, by using the blackbody radiation functions, that a blackbody at 293 K emits only 1.1% of its energy in the MWIR band and about 42.4% in the LWIR band. Therefore, MWIR band is more suitable for our goal of performing measurements of reflected IR radiation.

 

Fig. 1 The Planck curve for a blackbody at 293K (roughly room temperature), with the areas to be integrated for MWIR and LWIR sensors shaded.

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As we want to record reflected radiation, an artificial source is needed. An ideal source should be matched to the sensor, i.e. should emit mainly in the MWIR band, and should not induce a significant heating on the surface, to avoid increasing the emitted radiation.

A very simple yet effective source can be easily obtained by using an under-powered halogen lamp, which acts as a sort of MWIR source. By measuring its spectral emission, the lamp could be matched to the sensor; anyway good results are achieved by the simple rule-of-thumb of having no (or very faint) visible emission.

A TQR system (see Fig. 2 ) is quite simple: an IR source and a MWIR camera. The source was realized as described above. The MWIR camera was PtSi based with response sensitivity in the 3-5 μm. The sensor consists of 475 × 442 pixels, with a Stirling Cycle cooling and NETD of 0.2 K. Some care is needed during the measurements because many objects may act as IR sources leading to a non-uniform distribution of the IR radiation incident on the surface.

 

Fig. 2 A sketch of the experimental setup, detailing also the typical layered structure of a wall painting.

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NIR reflectography was performed for comparison. The device was a commercial digital camera (CMOS sensor of 3888 × 2592 pixels) which was modified for enhanced imaging over the full range 380-1150 nm, and then coupled to a suitable IR pass filter.

In conclusion, by working in the MWIR band and using a suitable MWIR source, the recorded IR radiation is dominated by the reflected energy, which, conversely, is strongly related to the surface properties.

3. Experimental results and discussion

As a first example, TQR was demonstrated in situ in the Chapel of Theodelinda, Duomo of Monza (Italy). The Chapel, currently under restoration, is entirely decorated by the extraordinary 15th century fresco cycle painted by the Zavattari family.

Figure 3 shows some results on a part (approximately 0.8 m × 1 m) of the walls. Gold and silver decorations, because of their high reflectivity, are very clearly outlined even in regions in which, both in the visible and in the NIR range, they are disguised by degraded or repainted surfaces. This ability to map gold and silver decorations in a quick and effective way is particularly useful when, as in this case, the frescos covered a large surface. The tool can also easily identify old restorations in which missed gold decorations were simply repainted. In this example, TQR imaging is also much better suited for visualizing the armor (look at the right hand of the soldier) than color and NIR photography.

 

Fig. 3 Part of the fresco by the Zavattaris in the Theodelinda’s Chapel. The artworks, executed between 1440 and 1446 are extremely rich and complex, featuring different fresco techniques, gold and silver decorations and reliefs. Color photography (a), and imaging in the NIR (b), compared to the TQR image (c).

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To further evaluate the TQR potential for in situ imaging, an investigation was performed, during museum opening hours, on “The Resurrection” by Piero della Francesca. “The Resurrection” (circa 1460) is a 2.25 m × 2 m mural fresco and tempera painting, housed in the Museo Civico of Sansepolcro (Italy). Figure 4 shows a detail of “The Resurrection”.

 

Fig. 4 “The Resurrection” by Piero della Francesca, circa 1460 (detail): color photography.

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MWIR imaging confirms its ability to differentiate materials and regions, as detailed in Fig. 5 . In particular, F and G are pigments, looking similar in the visible and only slightly different in the NIR (0.9 – 1.1 μm), which are clearly separated in TQR.

 

Fig. 5 “The Resurrection” by Piero della Francesca (detail): NIR image (left) and TQR image (right). A Original area; B and C painted integration; D Restoration plaster; E Green Earth pigment; F and G pigments with similar behavior in the visible and different reflectivity in MWIR.

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A different detail of “The Resurrection” is shown in Fig. 6 . Although TQR suffers from a relatively low spatial resolution, in comparison with color and NIR photography, very interesting features are identified, such as high reflective retouches (A) and tiny circular points on the edge of the shield (B). The most surprising feature was outlined on the soldier’s sword (C). With the help of the restorer, it turned out that this area was painted by using two different fresco techniques. Then TQR enables this subtle distinction, which is not detected by NIR photography.

 

Fig. 6 “The Resurrection” by Piero della Francesca (detail): NIR image (left) and TQR image (right). A retouches; B inhomogeneities on the shield; C Different execution techniques on the soldier’s sword, not detected in NIR; D better differentiation of the background in MWIR; E different reflectance NIR MWIR.

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In this work the results obtained by TQR have been compared with CMOS images in the range (0.9 – 1.1 μm). This is due to the fact that Thermal Quasi-Reflectography was devised for gaining a better differentiation of the surface materials. Longer inspection wavelength in the NIR (up to about 2 μm) are indisputably better to detect preparatory drawings and pentimenti, thanks to the increased transparency of the paint layers at these wavelengths, but may loose superficial features [15].

To gain further insight, an experiment was performed on a fresco model, dated around 1930, at the Opificio delle Pietre Dure (OPD) Restoration Laboratories in Florence (Italy). The results, shown in Fig. 7 , compare TQR with CMOS imaging and IR scanner [12] in the deep NIR at 1.82 μm.

 

Fig. 7 A fresco model, copied from Ghirlandaio, realized around 1930 by the restorer Benini. Color photography (a); CMOS NIR photography (0.9 – 1.1 μm) (b); IR scanner at 1.82 μm (c) and TQR image (mosaic of two views) (d).

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The MWIR response reveals complementary features that are not detectable in the NIR band, even at longer wavelengths. In particular, superficial features are detected such as the cinnabar secco finishing touches (the mouth), the superficial drawing traces in the contour face and the inhomogeneities on the hat and hair.

4. Conclusions

In this paper, a new tool in artwork imaging was proposed. The main idea of the new tool, which we called Thermal Quasi-Reflectography (TQR), is to record MWIR reflected by the object. Basically, we took the usual thermography measurement concept in reverse and, therefore, emitted radiation should be made negligible with respect to the reflected one.

We showed that, by using MWIR and a suitable source, at room temperature (i.e. safe for artworks) recorded radiation is largely dominated by reflected energy.

The TQR ability to characterize pictorial materials on artworks was demonstrated by performing imaging in situ on two famous artworks. In both cases, TQR provides very interesting results such as good pigment differentiations, selective mapping of gold and silver decorations and a clearer identification (with respect to NIR 0.9 – 1.1 μm reflectography) of retouches and painting integrations. In some cases, TQR provides identification of unique features, such as different execution techniques on some details of “The Resurrection”.

For mural paintings the use of MWIR region reveals to be crucial, making TQR a promising tool for the investigation of these artworks, where NIR imaging is less effective. Because of relatively low spatial resolution, better performance of the technique can be achieved by inspecting small areas; larger field of view (as in this paper) can be used as a first screening of the object.

Interesting areas for future refinements of TQR lie within the interaction with restorers and chemists. In fact, while not able of providing the analytic capability of infrared spectroscopy, TQR can be considered, to a certain extent, a simple yet effective means of obtaining a full-field, although integrated, infrared spectra of the surface. Future developments will also include the investigation of hyperspectral imaging in MWIR, whose first experiments are currently underway.

Acknowledgments

We wish to thank the Gaiani Foundation and the restorer Anna Lucchini for supporting the diagnostics in the Theodelinda’s Chapel and Mariangela Betti, Head of the Museum of Sansepolcro (Italy), for granting permission to carry out TQR experimentation on “The Resurrection” and for her enthusiastic supporting. Very special thanks are also due to Paola Ilaria Mariotti, restorer within the Opificio delle Pietre Dure (Florence, Italy), for introducing us to the magic and mystery of Piero della Francesca.

References and links

1. L. Carroll, The Annotated Alice: The Definitive Edition, Martin Gardner, ed. (W.W. Norton & Co., 1999), Chap. 1.

2. J. D. Barrow, Cosmic Imagery: Key Images in the History of Science (W.W. Norton & Co., 2008).

3. D. Paoletti and G. Schirripa Spagnolo, “Interferometric methods for artwork diagnostics” in Progress in Optics Vol. XXXV, E. Wolf, ed. (Elsevier, 1996).

4. V. Tornari, A. Bonarou, V. Zafiropulos, C. Fotakis, N. Smyrnakis, and S. Stassinopulos, “Structural evaluation of restoration processes with holographic diagnostic inspection,” J. Cult. Herit. 4, 347–354 (2003). [CrossRef]  

5. D. Ambrosini and D. Paoletti, “Holographic and speckle methods for the analysis of panel paintings. Developments since the early 1970s,” Rev. Conserv. 5, 38–48 (2004).

6. P. K. Rastogi, ed., Digital Speckle Pattern Interferometry and Related Techniques (Wiley, 2000).

7. P. M. Boone and V. B. Markov, “Examination of museum object by means of video holography,” Stud. Conserv. 40(2), 103–109 (1995). [CrossRef]  

8. G. Schirripa Spagnolo, D. Ambrosini, and G. Guattari, “Electro-optic holography system and digital image processing for in situ analysis of microclimate variations on artworks,” J. Opt. 28(3), 99–106 (1997). [CrossRef]  

9. J. Dulie-Barton, L. Dokos, D. Eastop, F. Lennard, A. R. Chambers, and M. Sahin, “Deformation and strain measurement techniques for the inspection of damage in works of art,” Rev. Conserv. 6, 63–73 (2005).

10. K. D. Hinsch, G. Gülker, and H. Helmers, “Checkup for aging artwork: optical tools to monitor mechanical behaviour,” Opt. Las. Engin. 45(5), 578–588 (2007). [CrossRef]  

11. J. R. J. van Asperen de Boer, “Infrared reflectography: a method for the examination of paintings,” Appl. Opt. 7(9), 1711–1714 (1968). [CrossRef]   [PubMed]  

12. C. Daffara and R. Fontana, “Multispectral infrared reflectography to differentiate features in paintings,” Microsc. Microanal. 17(5), 691–695 (2011). [CrossRef]   [PubMed]  

13. J. K. Delaney, J. G. Zeibel, M. Thoury, R. Littleton, M. Palmer, K. M. Morales, E. R. de la Rie, and A. Hoenigswald, “Visible and infrared imaging spectroscopy of Picasso’s Harlequin Musician: mapping and identification of artist materials in situ,” Appl. Spectrosc. 64(6), 584–594 (2010). [CrossRef]   [PubMed]  

14. X. Maldague, Theory and Practice of Infrared Technology for non destructive Testing (Wiley, 2001).

15. D. Ambrosini, C. Daffara, R. Di Biase, D. Paoletti, L. Pezzati, R. Bellucci, and F. Bettini, “Integrated reflectography and thermography for wooden paintings diagnostics,” J. Cult. Herit. 11(2), 196–204 (2010). [CrossRef]  

16. C. Daffara, L. Pezzati, D. Ambrosini, D. Paoletti, R. Di Biase, P. I. Mariotti, and C. Frosinini, “Wide-band IR imaging in the NIR-MIR-FIR regions for in-situ analysis of frescoes,” (invited paper), Proc. SPIE 8084, 8084061–80840612 (2011).

17. P. Targowski, B. Rouba, M. Wojtkowski, and A. Kowalczyk, “The application of optical coherence tomography to non-destructive examination of museum objects,” Stud. Conserv. 49, 107–114 (2004).

18. H. Liang, M. Cid, R. Cucu, G. Dobre, A. Podoleanu, J. Pedro, and D. Saunders, “En-face optical coherence tomography - a novel application of non-invasive imaging to art conservation,” Opt. Express 13, 6133–6144 (2005). [CrossRef]   [PubMed]  

19. T. Arecchi, M. Bellini, C. Corsi, R. Fontana, M. Materazzi, L. Pezzati, and A. Tortora, “A new tool for painting diagnostics: optical coherence tomography,” Opt. Spectrosc. 101(1), 23–26 (2006). [CrossRef]  

20. K. Fukunaga, Y. Ogawa, S. Hayashi, and I. Hosako, “Terahertz Spectroscopy for art conservation,” IEICE Electron. Express 4(8), 258–263 (2007). [CrossRef]  

21. A. J. L. Adam, P. C. Planken, S. Meloni, and J. Dik, “TeraHertz imaging of hidden paint layers on canvas,” Opt. Express 17(5), 3407–3416 (2009). [CrossRef]   [PubMed]  

22. M. R. Derrick, D. Stulik, and J. M. Landry, Infrared Spectroscopy in Conservation Science, (The Getty Conservation Institute, 1999).

References

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  1. L. Carroll, The Annotated Alice: The Definitive Edition, Martin Gardner, ed. (W.W. Norton & Co., 1999), Chap. 1.
  2. J. D. Barrow, Cosmic Imagery: Key Images in the History of Science (W.W. Norton & Co., 2008).
  3. D. Paoletti and G. Schirripa Spagnolo, “Interferometric methods for artwork diagnostics” in Progress in Optics Vol. XXXV, E. Wolf, ed. (Elsevier, 1996).
  4. V. Tornari, A. Bonarou, V. Zafiropulos, C. Fotakis, N. Smyrnakis, and S. Stassinopulos, “Structural evaluation of restoration processes with holographic diagnostic inspection,” J. Cult. Herit.4, 347–354 (2003).
    [CrossRef]
  5. D. Ambrosini and D. Paoletti, “Holographic and speckle methods for the analysis of panel paintings. Developments since the early 1970s,” Rev. Conserv.5, 38–48 (2004).
  6. P. K. Rastogi, ed., Digital Speckle Pattern Interferometry and Related Techniques (Wiley, 2000).
  7. P. M. Boone and V. B. Markov, “Examination of museum object by means of video holography,” Stud. Conserv.40(2), 103–109 (1995).
    [CrossRef]
  8. G. Schirripa Spagnolo, D. Ambrosini, and G. Guattari, “Electro-optic holography system and digital image processing for in situ analysis of microclimate variations on artworks,” J. Opt.28(3), 99–106 (1997).
    [CrossRef]
  9. J. Dulie-Barton, L. Dokos, D. Eastop, F. Lennard, A. R. Chambers, and M. Sahin, “Deformation and strain measurement techniques for the inspection of damage in works of art,” Rev. Conserv.6, 63–73 (2005).
  10. K. D. Hinsch, G. Gülker, and H. Helmers, “Checkup for aging artwork: optical tools to monitor mechanical behaviour,” Opt. Las. Engin.45(5), 578–588 (2007).
    [CrossRef]
  11. J. R. J. van Asperen de Boer, “Infrared reflectography: a method for the examination of paintings,” Appl. Opt.7(9), 1711–1714 (1968).
    [CrossRef] [PubMed]
  12. C. Daffara and R. Fontana, “Multispectral infrared reflectography to differentiate features in paintings,” Microsc. Microanal.17(5), 691–695 (2011).
    [CrossRef] [PubMed]
  13. J. K. Delaney, J. G. Zeibel, M. Thoury, R. Littleton, M. Palmer, K. M. Morales, E. R. de la Rie, and A. Hoenigswald, “Visible and infrared imaging spectroscopy of Picasso’s Harlequin Musician: mapping and identification of artist materials in situ,” Appl. Spectrosc.64(6), 584–594 (2010).
    [CrossRef] [PubMed]
  14. X. Maldague, Theory and Practice of Infrared Technology for non destructive Testing (Wiley, 2001).
  15. D. Ambrosini, C. Daffara, R. Di Biase, D. Paoletti, L. Pezzati, R. Bellucci, and F. Bettini, “Integrated reflectography and thermography for wooden paintings diagnostics,” J. Cult. Herit.11(2), 196–204 (2010).
    [CrossRef]
  16. C. Daffara, L. Pezzati, D. Ambrosini, D. Paoletti, R. Di Biase, P. I. Mariotti, and C. Frosinini, “Wide-band IR imaging in the NIR-MIR-FIR regions for in-situ analysis of frescoes,” (invited paper), Proc. SPIE8084, 8084061–80840612 (2011).
  17. P. Targowski, B. Rouba, M. Wojtkowski, and A. Kowalczyk, “The application of optical coherence tomography to non-destructive examination of museum objects,” Stud. Conserv.49, 107–114 (2004).
  18. H. Liang, M. Cid, R. Cucu, G. Dobre, A. Podoleanu, J. Pedro, and D. Saunders, “En-face optical coherence tomography - a novel application of non-invasive imaging to art conservation,” Opt. Express13, 6133–6144 (2005).
    [CrossRef] [PubMed]
  19. T. Arecchi, M. Bellini, C. Corsi, R. Fontana, M. Materazzi, L. Pezzati, and A. Tortora, “A new tool for painting diagnostics: optical coherence tomography,” Opt. Spectrosc.101(1), 23–26 (2006).
    [CrossRef]
  20. K. Fukunaga, Y. Ogawa, S. Hayashi, and I. Hosako, “Terahertz Spectroscopy for art conservation,” IEICE Electron. Express4(8), 258–263 (2007).
    [CrossRef]
  21. A. J. L. Adam, P. C. Planken, S. Meloni, and J. Dik, “TeraHertz imaging of hidden paint layers on canvas,” Opt. Express17(5), 3407–3416 (2009).
    [CrossRef] [PubMed]
  22. M. R. Derrick, D. Stulik, and J. M. Landry, Infrared Spectroscopy in Conservation Science, (The Getty Conservation Institute, 1999).

2011

C. Daffara, L. Pezzati, D. Ambrosini, D. Paoletti, R. Di Biase, P. I. Mariotti, and C. Frosinini, “Wide-band IR imaging in the NIR-MIR-FIR regions for in-situ analysis of frescoes,” (invited paper), Proc. SPIE8084, 8084061–80840612 (2011).

C. Daffara and R. Fontana, “Multispectral infrared reflectography to differentiate features in paintings,” Microsc. Microanal.17(5), 691–695 (2011).
[CrossRef] [PubMed]

2010

D. Ambrosini, C. Daffara, R. Di Biase, D. Paoletti, L. Pezzati, R. Bellucci, and F. Bettini, “Integrated reflectography and thermography for wooden paintings diagnostics,” J. Cult. Herit.11(2), 196–204 (2010).
[CrossRef]

J. K. Delaney, J. G. Zeibel, M. Thoury, R. Littleton, M. Palmer, K. M. Morales, E. R. de la Rie, and A. Hoenigswald, “Visible and infrared imaging spectroscopy of Picasso’s Harlequin Musician: mapping and identification of artist materials in situ,” Appl. Spectrosc.64(6), 584–594 (2010).
[CrossRef] [PubMed]

2009

2007

K. Fukunaga, Y. Ogawa, S. Hayashi, and I. Hosako, “Terahertz Spectroscopy for art conservation,” IEICE Electron. Express4(8), 258–263 (2007).
[CrossRef]

K. D. Hinsch, G. Gülker, and H. Helmers, “Checkup for aging artwork: optical tools to monitor mechanical behaviour,” Opt. Las. Engin.45(5), 578–588 (2007).
[CrossRef]

2006

T. Arecchi, M. Bellini, C. Corsi, R. Fontana, M. Materazzi, L. Pezzati, and A. Tortora, “A new tool for painting diagnostics: optical coherence tomography,” Opt. Spectrosc.101(1), 23–26 (2006).
[CrossRef]

2005

H. Liang, M. Cid, R. Cucu, G. Dobre, A. Podoleanu, J. Pedro, and D. Saunders, “En-face optical coherence tomography - a novel application of non-invasive imaging to art conservation,” Opt. Express13, 6133–6144 (2005).
[CrossRef] [PubMed]

J. Dulie-Barton, L. Dokos, D. Eastop, F. Lennard, A. R. Chambers, and M. Sahin, “Deformation and strain measurement techniques for the inspection of damage in works of art,” Rev. Conserv.6, 63–73 (2005).

2004

P. Targowski, B. Rouba, M. Wojtkowski, and A. Kowalczyk, “The application of optical coherence tomography to non-destructive examination of museum objects,” Stud. Conserv.49, 107–114 (2004).

D. Ambrosini and D. Paoletti, “Holographic and speckle methods for the analysis of panel paintings. Developments since the early 1970s,” Rev. Conserv.5, 38–48 (2004).

2003

V. Tornari, A. Bonarou, V. Zafiropulos, C. Fotakis, N. Smyrnakis, and S. Stassinopulos, “Structural evaluation of restoration processes with holographic diagnostic inspection,” J. Cult. Herit.4, 347–354 (2003).
[CrossRef]

1997

G. Schirripa Spagnolo, D. Ambrosini, and G. Guattari, “Electro-optic holography system and digital image processing for in situ analysis of microclimate variations on artworks,” J. Opt.28(3), 99–106 (1997).
[CrossRef]

1995

P. M. Boone and V. B. Markov, “Examination of museum object by means of video holography,” Stud. Conserv.40(2), 103–109 (1995).
[CrossRef]

1968

Adam, A. J. L.

Ambrosini, D.

C. Daffara, L. Pezzati, D. Ambrosini, D. Paoletti, R. Di Biase, P. I. Mariotti, and C. Frosinini, “Wide-band IR imaging in the NIR-MIR-FIR regions for in-situ analysis of frescoes,” (invited paper), Proc. SPIE8084, 8084061–80840612 (2011).

D. Ambrosini, C. Daffara, R. Di Biase, D. Paoletti, L. Pezzati, R. Bellucci, and F. Bettini, “Integrated reflectography and thermography for wooden paintings diagnostics,” J. Cult. Herit.11(2), 196–204 (2010).
[CrossRef]

D. Ambrosini and D. Paoletti, “Holographic and speckle methods for the analysis of panel paintings. Developments since the early 1970s,” Rev. Conserv.5, 38–48 (2004).

G. Schirripa Spagnolo, D. Ambrosini, and G. Guattari, “Electro-optic holography system and digital image processing for in situ analysis of microclimate variations on artworks,” J. Opt.28(3), 99–106 (1997).
[CrossRef]

Arecchi, T.

T. Arecchi, M. Bellini, C. Corsi, R. Fontana, M. Materazzi, L. Pezzati, and A. Tortora, “A new tool for painting diagnostics: optical coherence tomography,” Opt. Spectrosc.101(1), 23–26 (2006).
[CrossRef]

Bellini, M.

T. Arecchi, M. Bellini, C. Corsi, R. Fontana, M. Materazzi, L. Pezzati, and A. Tortora, “A new tool for painting diagnostics: optical coherence tomography,” Opt. Spectrosc.101(1), 23–26 (2006).
[CrossRef]

Bellucci, R.

D. Ambrosini, C. Daffara, R. Di Biase, D. Paoletti, L. Pezzati, R. Bellucci, and F. Bettini, “Integrated reflectography and thermography for wooden paintings diagnostics,” J. Cult. Herit.11(2), 196–204 (2010).
[CrossRef]

Bettini, F.

D. Ambrosini, C. Daffara, R. Di Biase, D. Paoletti, L. Pezzati, R. Bellucci, and F. Bettini, “Integrated reflectography and thermography for wooden paintings diagnostics,” J. Cult. Herit.11(2), 196–204 (2010).
[CrossRef]

Bonarou, A.

V. Tornari, A. Bonarou, V. Zafiropulos, C. Fotakis, N. Smyrnakis, and S. Stassinopulos, “Structural evaluation of restoration processes with holographic diagnostic inspection,” J. Cult. Herit.4, 347–354 (2003).
[CrossRef]

Boone, P. M.

P. M. Boone and V. B. Markov, “Examination of museum object by means of video holography,” Stud. Conserv.40(2), 103–109 (1995).
[CrossRef]

Chambers, A. R.

J. Dulie-Barton, L. Dokos, D. Eastop, F. Lennard, A. R. Chambers, and M. Sahin, “Deformation and strain measurement techniques for the inspection of damage in works of art,” Rev. Conserv.6, 63–73 (2005).

Cid, M.

Corsi, C.

T. Arecchi, M. Bellini, C. Corsi, R. Fontana, M. Materazzi, L. Pezzati, and A. Tortora, “A new tool for painting diagnostics: optical coherence tomography,” Opt. Spectrosc.101(1), 23–26 (2006).
[CrossRef]

Cucu, R.

Daffara, C.

C. Daffara and R. Fontana, “Multispectral infrared reflectography to differentiate features in paintings,” Microsc. Microanal.17(5), 691–695 (2011).
[CrossRef] [PubMed]

C. Daffara, L. Pezzati, D. Ambrosini, D. Paoletti, R. Di Biase, P. I. Mariotti, and C. Frosinini, “Wide-band IR imaging in the NIR-MIR-FIR regions for in-situ analysis of frescoes,” (invited paper), Proc. SPIE8084, 8084061–80840612 (2011).

D. Ambrosini, C. Daffara, R. Di Biase, D. Paoletti, L. Pezzati, R. Bellucci, and F. Bettini, “Integrated reflectography and thermography for wooden paintings diagnostics,” J. Cult. Herit.11(2), 196–204 (2010).
[CrossRef]

de la Rie, E. R.

Delaney, J. K.

Di Biase, R.

C. Daffara, L. Pezzati, D. Ambrosini, D. Paoletti, R. Di Biase, P. I. Mariotti, and C. Frosinini, “Wide-band IR imaging in the NIR-MIR-FIR regions for in-situ analysis of frescoes,” (invited paper), Proc. SPIE8084, 8084061–80840612 (2011).

D. Ambrosini, C. Daffara, R. Di Biase, D. Paoletti, L. Pezzati, R. Bellucci, and F. Bettini, “Integrated reflectography and thermography for wooden paintings diagnostics,” J. Cult. Herit.11(2), 196–204 (2010).
[CrossRef]

Dik, J.

Dobre, G.

Dokos, L.

J. Dulie-Barton, L. Dokos, D. Eastop, F. Lennard, A. R. Chambers, and M. Sahin, “Deformation and strain measurement techniques for the inspection of damage in works of art,” Rev. Conserv.6, 63–73 (2005).

Dulie-Barton, J.

J. Dulie-Barton, L. Dokos, D. Eastop, F. Lennard, A. R. Chambers, and M. Sahin, “Deformation and strain measurement techniques for the inspection of damage in works of art,” Rev. Conserv.6, 63–73 (2005).

Eastop, D.

J. Dulie-Barton, L. Dokos, D. Eastop, F. Lennard, A. R. Chambers, and M. Sahin, “Deformation and strain measurement techniques for the inspection of damage in works of art,” Rev. Conserv.6, 63–73 (2005).

Fontana, R.

C. Daffara and R. Fontana, “Multispectral infrared reflectography to differentiate features in paintings,” Microsc. Microanal.17(5), 691–695 (2011).
[CrossRef] [PubMed]

T. Arecchi, M. Bellini, C. Corsi, R. Fontana, M. Materazzi, L. Pezzati, and A. Tortora, “A new tool for painting diagnostics: optical coherence tomography,” Opt. Spectrosc.101(1), 23–26 (2006).
[CrossRef]

Fotakis, C.

V. Tornari, A. Bonarou, V. Zafiropulos, C. Fotakis, N. Smyrnakis, and S. Stassinopulos, “Structural evaluation of restoration processes with holographic diagnostic inspection,” J. Cult. Herit.4, 347–354 (2003).
[CrossRef]

Frosinini, C.

C. Daffara, L. Pezzati, D. Ambrosini, D. Paoletti, R. Di Biase, P. I. Mariotti, and C. Frosinini, “Wide-band IR imaging in the NIR-MIR-FIR regions for in-situ analysis of frescoes,” (invited paper), Proc. SPIE8084, 8084061–80840612 (2011).

Fukunaga, K.

K. Fukunaga, Y. Ogawa, S. Hayashi, and I. Hosako, “Terahertz Spectroscopy for art conservation,” IEICE Electron. Express4(8), 258–263 (2007).
[CrossRef]

Guattari, G.

G. Schirripa Spagnolo, D. Ambrosini, and G. Guattari, “Electro-optic holography system and digital image processing for in situ analysis of microclimate variations on artworks,” J. Opt.28(3), 99–106 (1997).
[CrossRef]

Gülker, G.

K. D. Hinsch, G. Gülker, and H. Helmers, “Checkup for aging artwork: optical tools to monitor mechanical behaviour,” Opt. Las. Engin.45(5), 578–588 (2007).
[CrossRef]

Hayashi, S.

K. Fukunaga, Y. Ogawa, S. Hayashi, and I. Hosako, “Terahertz Spectroscopy for art conservation,” IEICE Electron. Express4(8), 258–263 (2007).
[CrossRef]

Helmers, H.

K. D. Hinsch, G. Gülker, and H. Helmers, “Checkup for aging artwork: optical tools to monitor mechanical behaviour,” Opt. Las. Engin.45(5), 578–588 (2007).
[CrossRef]

Hinsch, K. D.

K. D. Hinsch, G. Gülker, and H. Helmers, “Checkup for aging artwork: optical tools to monitor mechanical behaviour,” Opt. Las. Engin.45(5), 578–588 (2007).
[CrossRef]

Hoenigswald, A.

Hosako, I.

K. Fukunaga, Y. Ogawa, S. Hayashi, and I. Hosako, “Terahertz Spectroscopy for art conservation,” IEICE Electron. Express4(8), 258–263 (2007).
[CrossRef]

Kowalczyk, A.

P. Targowski, B. Rouba, M. Wojtkowski, and A. Kowalczyk, “The application of optical coherence tomography to non-destructive examination of museum objects,” Stud. Conserv.49, 107–114 (2004).

Lennard, F.

J. Dulie-Barton, L. Dokos, D. Eastop, F. Lennard, A. R. Chambers, and M. Sahin, “Deformation and strain measurement techniques for the inspection of damage in works of art,” Rev. Conserv.6, 63–73 (2005).

Liang, H.

Littleton, R.

Mariotti, P. I.

C. Daffara, L. Pezzati, D. Ambrosini, D. Paoletti, R. Di Biase, P. I. Mariotti, and C. Frosinini, “Wide-band IR imaging in the NIR-MIR-FIR regions for in-situ analysis of frescoes,” (invited paper), Proc. SPIE8084, 8084061–80840612 (2011).

Markov, V. B.

P. M. Boone and V. B. Markov, “Examination of museum object by means of video holography,” Stud. Conserv.40(2), 103–109 (1995).
[CrossRef]

Materazzi, M.

T. Arecchi, M. Bellini, C. Corsi, R. Fontana, M. Materazzi, L. Pezzati, and A. Tortora, “A new tool for painting diagnostics: optical coherence tomography,” Opt. Spectrosc.101(1), 23–26 (2006).
[CrossRef]

Meloni, S.

Morales, K. M.

Ogawa, Y.

K. Fukunaga, Y. Ogawa, S. Hayashi, and I. Hosako, “Terahertz Spectroscopy for art conservation,” IEICE Electron. Express4(8), 258–263 (2007).
[CrossRef]

Palmer, M.

Paoletti, D.

C. Daffara, L. Pezzati, D. Ambrosini, D. Paoletti, R. Di Biase, P. I. Mariotti, and C. Frosinini, “Wide-band IR imaging in the NIR-MIR-FIR regions for in-situ analysis of frescoes,” (invited paper), Proc. SPIE8084, 8084061–80840612 (2011).

D. Ambrosini, C. Daffara, R. Di Biase, D. Paoletti, L. Pezzati, R. Bellucci, and F. Bettini, “Integrated reflectography and thermography for wooden paintings diagnostics,” J. Cult. Herit.11(2), 196–204 (2010).
[CrossRef]

D. Ambrosini and D. Paoletti, “Holographic and speckle methods for the analysis of panel paintings. Developments since the early 1970s,” Rev. Conserv.5, 38–48 (2004).

Pedro, J.

Pezzati, L.

C. Daffara, L. Pezzati, D. Ambrosini, D. Paoletti, R. Di Biase, P. I. Mariotti, and C. Frosinini, “Wide-band IR imaging in the NIR-MIR-FIR regions for in-situ analysis of frescoes,” (invited paper), Proc. SPIE8084, 8084061–80840612 (2011).

D. Ambrosini, C. Daffara, R. Di Biase, D. Paoletti, L. Pezzati, R. Bellucci, and F. Bettini, “Integrated reflectography and thermography for wooden paintings diagnostics,” J. Cult. Herit.11(2), 196–204 (2010).
[CrossRef]

T. Arecchi, M. Bellini, C. Corsi, R. Fontana, M. Materazzi, L. Pezzati, and A. Tortora, “A new tool for painting diagnostics: optical coherence tomography,” Opt. Spectrosc.101(1), 23–26 (2006).
[CrossRef]

Planken, P. C.

Podoleanu, A.

Rouba, B.

P. Targowski, B. Rouba, M. Wojtkowski, and A. Kowalczyk, “The application of optical coherence tomography to non-destructive examination of museum objects,” Stud. Conserv.49, 107–114 (2004).

Sahin, M.

J. Dulie-Barton, L. Dokos, D. Eastop, F. Lennard, A. R. Chambers, and M. Sahin, “Deformation and strain measurement techniques for the inspection of damage in works of art,” Rev. Conserv.6, 63–73 (2005).

Saunders, D.

Schirripa Spagnolo, G.

G. Schirripa Spagnolo, D. Ambrosini, and G. Guattari, “Electro-optic holography system and digital image processing for in situ analysis of microclimate variations on artworks,” J. Opt.28(3), 99–106 (1997).
[CrossRef]

Smyrnakis, N.

V. Tornari, A. Bonarou, V. Zafiropulos, C. Fotakis, N. Smyrnakis, and S. Stassinopulos, “Structural evaluation of restoration processes with holographic diagnostic inspection,” J. Cult. Herit.4, 347–354 (2003).
[CrossRef]

Stassinopulos, S.

V. Tornari, A. Bonarou, V. Zafiropulos, C. Fotakis, N. Smyrnakis, and S. Stassinopulos, “Structural evaluation of restoration processes with holographic diagnostic inspection,” J. Cult. Herit.4, 347–354 (2003).
[CrossRef]

Targowski, P.

P. Targowski, B. Rouba, M. Wojtkowski, and A. Kowalczyk, “The application of optical coherence tomography to non-destructive examination of museum objects,” Stud. Conserv.49, 107–114 (2004).

Thoury, M.

Tornari, V.

V. Tornari, A. Bonarou, V. Zafiropulos, C. Fotakis, N. Smyrnakis, and S. Stassinopulos, “Structural evaluation of restoration processes with holographic diagnostic inspection,” J. Cult. Herit.4, 347–354 (2003).
[CrossRef]

Tortora, A.

T. Arecchi, M. Bellini, C. Corsi, R. Fontana, M. Materazzi, L. Pezzati, and A. Tortora, “A new tool for painting diagnostics: optical coherence tomography,” Opt. Spectrosc.101(1), 23–26 (2006).
[CrossRef]

van Asperen de Boer, J. R. J.

Wojtkowski, M.

P. Targowski, B. Rouba, M. Wojtkowski, and A. Kowalczyk, “The application of optical coherence tomography to non-destructive examination of museum objects,” Stud. Conserv.49, 107–114 (2004).

Zafiropulos, V.

V. Tornari, A. Bonarou, V. Zafiropulos, C. Fotakis, N. Smyrnakis, and S. Stassinopulos, “Structural evaluation of restoration processes with holographic diagnostic inspection,” J. Cult. Herit.4, 347–354 (2003).
[CrossRef]

Zeibel, J. G.

Appl. Opt.

Appl. Spectrosc.

IEICE Electron. Express

K. Fukunaga, Y. Ogawa, S. Hayashi, and I. Hosako, “Terahertz Spectroscopy for art conservation,” IEICE Electron. Express4(8), 258–263 (2007).
[CrossRef]

J. Cult. Herit.

D. Ambrosini, C. Daffara, R. Di Biase, D. Paoletti, L. Pezzati, R. Bellucci, and F. Bettini, “Integrated reflectography and thermography for wooden paintings diagnostics,” J. Cult. Herit.11(2), 196–204 (2010).
[CrossRef]

V. Tornari, A. Bonarou, V. Zafiropulos, C. Fotakis, N. Smyrnakis, and S. Stassinopulos, “Structural evaluation of restoration processes with holographic diagnostic inspection,” J. Cult. Herit.4, 347–354 (2003).
[CrossRef]

J. Opt.

G. Schirripa Spagnolo, D. Ambrosini, and G. Guattari, “Electro-optic holography system and digital image processing for in situ analysis of microclimate variations on artworks,” J. Opt.28(3), 99–106 (1997).
[CrossRef]

Microsc. Microanal.

C. Daffara and R. Fontana, “Multispectral infrared reflectography to differentiate features in paintings,” Microsc. Microanal.17(5), 691–695 (2011).
[CrossRef] [PubMed]

Opt. Express

Opt. Las. Engin.

K. D. Hinsch, G. Gülker, and H. Helmers, “Checkup for aging artwork: optical tools to monitor mechanical behaviour,” Opt. Las. Engin.45(5), 578–588 (2007).
[CrossRef]

Opt. Spectrosc.

T. Arecchi, M. Bellini, C. Corsi, R. Fontana, M. Materazzi, L. Pezzati, and A. Tortora, “A new tool for painting diagnostics: optical coherence tomography,” Opt. Spectrosc.101(1), 23–26 (2006).
[CrossRef]

Proc. SPIE

C. Daffara, L. Pezzati, D. Ambrosini, D. Paoletti, R. Di Biase, P. I. Mariotti, and C. Frosinini, “Wide-band IR imaging in the NIR-MIR-FIR regions for in-situ analysis of frescoes,” (invited paper), Proc. SPIE8084, 8084061–80840612 (2011).

Rev. Conserv.

J. Dulie-Barton, L. Dokos, D. Eastop, F. Lennard, A. R. Chambers, and M. Sahin, “Deformation and strain measurement techniques for the inspection of damage in works of art,” Rev. Conserv.6, 63–73 (2005).

D. Ambrosini and D. Paoletti, “Holographic and speckle methods for the analysis of panel paintings. Developments since the early 1970s,” Rev. Conserv.5, 38–48 (2004).

Stud. Conserv.

P. Targowski, B. Rouba, M. Wojtkowski, and A. Kowalczyk, “The application of optical coherence tomography to non-destructive examination of museum objects,” Stud. Conserv.49, 107–114 (2004).

P. M. Boone and V. B. Markov, “Examination of museum object by means of video holography,” Stud. Conserv.40(2), 103–109 (1995).
[CrossRef]

Other

M. R. Derrick, D. Stulik, and J. M. Landry, Infrared Spectroscopy in Conservation Science, (The Getty Conservation Institute, 1999).

P. K. Rastogi, ed., Digital Speckle Pattern Interferometry and Related Techniques (Wiley, 2000).

L. Carroll, The Annotated Alice: The Definitive Edition, Martin Gardner, ed. (W.W. Norton & Co., 1999), Chap. 1.

J. D. Barrow, Cosmic Imagery: Key Images in the History of Science (W.W. Norton & Co., 2008).

D. Paoletti and G. Schirripa Spagnolo, “Interferometric methods for artwork diagnostics” in Progress in Optics Vol. XXXV, E. Wolf, ed. (Elsevier, 1996).

X. Maldague, Theory and Practice of Infrared Technology for non destructive Testing (Wiley, 2001).

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Figures (7)

Fig. 1
Fig. 1

The Planck curve for a blackbody at 293K (roughly room temperature), with the areas to be integrated for MWIR and LWIR sensors shaded.

Fig. 2
Fig. 2

A sketch of the experimental setup, detailing also the typical layered structure of a wall painting.

Fig. 3
Fig. 3

Part of the fresco by the Zavattaris in the Theodelinda’s Chapel. The artworks, executed between 1440 and 1446 are extremely rich and complex, featuring different fresco techniques, gold and silver decorations and reliefs. Color photography (a), and imaging in the NIR (b), compared to the TQR image (c).

Fig. 4
Fig. 4

“The Resurrection” by Piero della Francesca, circa 1460 (detail): color photography.

Fig. 5
Fig. 5

“The Resurrection” by Piero della Francesca (detail): NIR image (left) and TQR image (right). A Original area; B and C painted integration; D Restoration plaster; E Green Earth pigment; F and G pigments with similar behavior in the visible and different reflectivity in MWIR.

Fig. 6
Fig. 6

“The Resurrection” by Piero della Francesca (detail): NIR image (left) and TQR image (right). A retouches; B inhomogeneities on the shield; C Different execution techniques on the soldier’s sword, not detected in NIR; D better differentiation of the background in MWIR; E different reflectance NIR MWIR.

Fig. 7
Fig. 7

A fresco model, copied from Ghirlandaio, realized around 1930 by the restorer Benini. Color photography (a); CMOS NIR photography (0.9 – 1.1 μm) (b); IR scanner at 1.82 μm (c) and TQR image (mosaic of two views) (d).

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