Reflectance Transformation Imaging (RTI)

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Reflectance Transformation Imaging (RTI) is a Computational Photography assisted technique, which uses multi-lighting conditions to capture a set of images, from a fixed camera position, with the aim of virtually and interactively revealing the characteristics of an imaged surface.

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What is RTI[edit | edit source]

RTI (Reflectance Transformation Imaging) is a user-friendly, non-invasive imaging technique for the examination and documentation of cultural heritage object surfaces. In this technique, a source image set is processed into an interactive file. It allows the viewer to examine the visual appearance of an object in various lighting conditions with a range of computational enhancements, highlighting and revealing characteristics of the imaged object. Applications using this technique range from simple, accessible tools to highly calibrated scientific systems. RTI can be used for a variety of activities including documentation, access, condition monitoring, interventive conservation treatment, interactive museum displays, and research. The distinctive feature of this method is the ability to virtually relight the imaged surface from any raking angle in a viewer interface. A processed source image set is therefore often referred to as a relightable file or image.

Key to this imaging method is the acquisition of the source image set; a series of images are captured with the object and camera static relative to each other, while knowing or recording the spatial location of the light sources.

The following steps/conditions are essential to this method:

A. A camera is mounted on top of a physical or imaginary hemispherical umbrella/dome facing the object.
B. A series of individual images are captured, each lit (with a flash or continuous light source) from varying directions following the shape of a physical or imaginary umbrella/dome. These images can be many of the same light sources, all with fixed positions, homogeneously distributed, or a single light source to be manually repositioned.
C. Throughout the recording process, both the camera and object stay 100% motionless.
D. The distance from the light source to the imaged object is consistent throughout all recordings.
E. Throughout the acquisition process, the spatial position of the applied light sources is registered (highlight method) or it is predetermined and incorporated into the processing software (some of the dome methods).
F. The obtained source image set is processed into a relightable image with appropriate software.

Other more general terms for this acquisition method are also in use, i.e. Single Camera Multi Light (SCML) and Multi-light Reflectance (MLR). See the Setup section for a more detailed overview on the various types of acquisition systems (dome, highlight, rotating arm, and microscopic methods), equipment, and setups.

Theoretical model of a Single Camera Multi Light (SCML) dome acquisition device with, in this case, 108 fixed light positions on its interior, made in SketchUp Make 2016, Hendrik Hameeuw 2021

Schematic of a virtual dome for highlight RTI (H-RTI) indicating four angles of light and twelve locations around the object for a manually positioned light source, made in Adobe Illustrator CC, Emily Frank 2021

SCML methods such as RTI use of multiple angles of illumination to understand the reflectance and topographical information of the surface of interest. The most common implementation of RTI is via Polynomial Texture Mapping (PTM) invented by Tom Malzbender of HP Labs in 2000 (Maelzbender et al. 2000, Maelzbender et al. 2001) and HSH (Hemispherical Harmonics) RTI introduced for heritage applications by 2008. Since, these types of interactive imaging have been applied to a range of art and cultural assets in a wide variety of situations (see also the History section) (Mudge et al. 2008, Earl et al. 2010, Klausmeyer et al. 2012, Mudge et al. 2006).

Key to the computer assistance in SCML/MLR techniques is that the position of the light source in each image be known. When the camera/multi-light combination system is aligned in a fixed setup (such as a dome, with a rotating arm, and/or under a microscope), the information about the light positions can be included in the processing software beforehand. In other cases (methods relying on the highlight method), each photograph in the source image set needs to include a reflective sphere. It allows the processing software to keep track of the position of the light source in each shot; this crucial information to be extracted and used during the processing phase. This lighting information is used to generate a mathematical model of the surface of interest. More technically, the RTI method derives a per-pixel reflectance model represented by a set of coefficients that defines the fitted function that takes into account the direction of the lighting (Manfredi et al. 2014, LOC RTI Format Description Properties). Other SCML/MLR methods follow similar calculation methods. See the Other Multi-light Reflectance Technologies section for the functionality and differences of each of these methods.

The resulting relightable images are processed from a source image set by custom built software (e.g. RTIBuilder) to calculate and establish the interactive value (function) for each pixel. Missing illumination angles are interpolated from the available incident lighting angles and registered in the source image set to fully model the surface’s interaction with light. For each pixel, the surface reflectance is approximated. The result is what can be described as a virtual relightable object, which can mimic any raking light condition. Secondly, various rendering modes reveal, accentuate, and document details on the imaged surface. These outcomes can be consulted in viewer interfaces, which can be stand alone or web-based (e.g. RTIViewer, WebRTIViewer, Pixel+ viewer). When uploaded, all pixel information is mapped with the same resolution as the original photographic captures. The viewers allow the operator to move the virtual light sources over the imaged surface providing unique diagnostic illuminations that would be difficult to obtain by inspecting individual or standardized still-images, and often even surpass visual inspections of the original objects. Furthermore, processed relightable files can be embedded in web pages or combined with additional imaging methods to present multi-faceted investigations of surface topography and other features of art of cultural assets ( Artal-Isbrand et al. 2011, Caine et al. 2011, Hanneken 2016, Watteeuw et al. 2020). Advanced viewer interfaces allow annotations and layered disseminations. Some have the option to generate high-quality screen captures of any particular visualisation at the desire of the operator, to be used for dissemination. See the Viewers section for an extensive overview.

Since its introduction early/mid 2000s, and thanks to the launch of the open access processing and viewing software by Cultural Heritage Imaging (see History below ), RTI and other SCML/MLR methods have been implemented by a large number of cultural institutions, conservators, conservation scientists, research units, and individuals around the world. Many digital repositories include relightable files, and countless applications and workflows have been developed using this imaging technology. In conservation practice, these methods have been used to examine and track surface condition (Hughes-Hallett et al. 2020), document and understand methods of manufacture, (i.e. via study of tool marks, etc.) (Harris and Piquette 2015, Artal-Isbrand 2010, Serotta 2014), and record ephemeral and in situ phenomena (i.e. rock art, archaeological textile impressions, etc.) (Duffy 2018, Frank 2017).

History of RTI[edit | edit source]

RTI setups[edit | edit source]

Equipment lists[edit | edit source]

Workflows[edit | edit source]

Related multi-light technologies[edit | edit source]

Terminology[edit | edit source]

PS (Photometric Studio)[edit | edit source]

HSH RTI (Hemispherical Harmonics)[edit | edit source]

PTM (Polynomial Texture Mapping)[edit | edit source]

RBF RTI (Radial Basis Function)[edit | edit source]

DMD (Discrete Modal Decomposition)[edit | edit source]

Difference between these[edit | edit source]

Data[edit | edit source]

Creation (capture data)[edit | edit source]

Processing[edit | edit source]

Metadating[edit | edit source]

Quality[edit | edit source]

File types (consultation data)[edit | edit source]

Dissemination / RTI Viewers[edit | edit source]

Stand-alone/desktop viewers[edit | edit source]

Web-based viewers[edit | edit source]

Embedding webpages and online databases[edit | edit source]

Technical Support / Obsolescence[edit | edit source]

Recurring challenges[edit | edit source]

Solutions[edit | edit source]

Case Studies[edit | edit source]

General[edit | edit source]

Specific for Conservation Sciences[edit | edit source]

RTI in combination with other imaging technologies[edit | edit source]

UV[edit | edit source]

IR[edit | edit source]

3D[edit | edit source]

Bibliography / Suggested Reading[edit | edit source]

Artal-Isbrand, P. et al. 2010. “An Evaluation of Decorative Techniques on a Red-Figure Attic Vase from the Worcester Art Museum using Reflectance Transformation Imaging (RTI) and Confocal Microscopy with a Special Focus on the ‘Relief Line’.” MRS Proceedings 1319.

Artal-Isbrand, P., P. Klausmeyer, and W. Murray 2011. “An Evaluation of Decorative Techniques on a Red-Figure Attic Vase from the Worcester Art Museum using Reflectance Transformation Imaging (RTI) and Confocal Microscopy with a Special Focus on the ‘Relief Line’.” in: MRS Online Proceeding Library Archive 1319.

Caine, M. and M. Magen. 2011. “Pixels and Parchment: The Application of RTI and Infrared Imaging to the Dead Sea Scrolls.” In Electronic Visualisation and the Arts (EVA 2011), edited by Stuart Dunn, Jonathan P. Bowen and Kia Ng, 140–146. London: BCS.

Duffy, S. 2018. Multi-light Imaging for Cultural Heritage. Swindon: Historic England.
Earl, G.P., K. Martinez, and T. Malzbender. Archaeological Applications of Polynomial Texture Mapping: Analysis, Conservation and Representation. J. Archaeol. Sci. 2010, 37, 2040–2050.

Frank, E. 2017. “Lights, Camera, Archaeology: Documenting Archaeological Textile Impressions with Reflectance Transformation Imaging (RTI).” Textile Specialty Group Postprints 25. The American Institute for Conservation, 11-42.

Hanneken, T. 2016. “New Technology for Imaging Unreadable Manuscripts and Other Artifacts: Integrated Spectral Reflectance Transformation Imaging (Spectral RTI).” In Ancient Worlds in a Digital Culture, edited by Claire Clivaz and David Hamidovic, 180–195. Digital Biblical Studies 1. Leiden: Brill.

Harris, S. and K. Piquette. 2015. “Reflectance Transformation Imaging (RTI) for visualising leather grain surface morphology as an aid to species identification: a pilot study.” Archaeological Leather Group Newsletter 42: 13-18.
Hughes-Hallett, M., C. Young, and P. Messier. 2020. “A Review of RTI and an Investigation into the Applicability of Micro-RTI as a Tool for the Documentation and Conservation of Modern and Contemporary Paintings.” Journal of the American Institute for Conservation.

Klausmeyer, P., R. Albertson, M. Cushman, and P. Artal-Isbrand. Applications of Reflectance Transformation Imaging (RTI) in a Fine Arts Museum: Examination, Documentation, and Beyond. Available online: (accessed on 13 June 2014).

Malzbender, T., D. Gelb, H. Wolters, and B. Zuckerman. Enhancement of Shape Perception by Surface Reflectance Transformation. Available online: (accessed on 9 July 2014)

Malzbender, T., D. Gelb, and H. Wolters. Polynomial Texture Maps. In Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques, Los Angeles, CA, USA, 12–17 August 2001; pp. 519–528.

Mark M., T. Malzbender, A. Chalmers, R. Scopigno, J. Davis, O. Wang, P. Gunawardane, M. Ashley, M. Doerr, A. Proenca, and J. Barbosa. 2008. Image-based empirical information acquisition, scientific reliability, and long-term digital preservation for the natural sciences and cultural heritage. In (Eurographics’08) Tutorials, M. Roussou and J. Leigh, Eds., Eurographics Association. (accessed on 10 March 2021)

Manfredi, M., G. Bearman, G. Williamson, D. Kronkright, E. Doehne, M. Jacobs, and E. Marengo. “A New Quantitative Method for the Non-Invasive Documentation of Morphological Damage in Paintings Using RTI Surface Normals.” Sensors 14, no. 7 (2014): 12271–84. doi:10.3390/S140712271.

Mudge, M., T. Malzbender, C. Schroer, and M. Lum. New Reflection Transformation Imaging Methods for Rock Art and Multiple-Viewpoint Display. Available online: (accessed on 13 June 2014).

Serotta, A. 2014. “An Investigation of Tool Marks on Ancient Egyptian Hard Stone Sculpture: Preliminary Report.” Metropolitan Museum of Art Studies in Science and Technology 2. New York: The Metropolitan Museum of Art, 197-201.

Watteeuw, L., M. Van Bos, T. Gersten, B. Vandermeulen, and H. Hameeuw. 2020. An applied complementary use of Macro X-ray Fluorescence scanning and Multi-light reflectance imaging to study Medieval Illuminated Manuscripts. The Rijmbijbel of Jacob van Maerlant, in: Microchemical Journal 155 (June 2020), 104582. (DOI: 10.1016/j.microc.2019.104582)

RTI Format Description Properties: (accessed on 29 March 2021) (accessed on 29 March 2021). (accessed on 29 March 2021). (accessed on 29 March 2021). (accessed on 29 March 2021).