technical writing
Reading Between the Pages: The Development & Use of Spectral Imaging Technology By Alan Smithee 3/25/2016 Introduction: What is Spectral Imaging? Spectral imaging provides access to a world beyond the scope of the human eye. With this specialized technology, we can identify and distinguish landscape features, collect data on distant stars, or even read the pages of an ancient book without opening the cover. Sometimes referred to as hyperspectral imaging, spectral imaging is a form of photography that “provides a digital image with far more spectral (color) information for each pixel than traditional color cameras” [1]. The objective of this report is to help readers understand how this technology evolved, how it works, and how various professionals have adapted it to meet the needs of their respective industries. Additionally, the conclusion will suggest further avenues for research. History & Development of Spectroscopy In 1666, Sir Isaac Newton coined the term spectrum to describe the bands of color created when white light from the sun passes through a glass prism; his equipment—a lens, a prism, and screen—formed the basis of modern spectroscopes [2, Fig.1]. The early 1800s would see multiple significant advances in the field when J.W. Ritter observed the ultraviolet properties of sun light, W. Herschel examined the infrared properties, and Joseph Fraunhofer identified dark lines crossing the sun’s spectrum. By 1859, G. Kirchoff and R. Bunsen established that even individual molecules have a unique spectrum [3]. ( Figure 1: Newton’s spectroscope. Sunlight (Z), enters the window, passes through the prism, and projects the color spectrum onto a screen (P). Source: Spectrum-Newton. ( n.d .). ChemTeam . Retrieved 3/10/16 from http://www.chemteam.info/Electrons/Spectrum-History.html ) The advent of the laser in the 1900s offered scientists a tool with more “intense,” focused radiation. This allowed for even more refined and accurate measurements. Notable researchers of this era include Basov and Prokhorov, whose microwave oscillator (or “maser”) in the 1950s was a precursor for the modern laser; T.H. Maiman who developed the ruby laser in 1960; and Schawlow, Javan, and Lamb, Jr., who pioneered techniques for ultra-high resolution spectroscopy [4]. How Does it Work? Spectral imaging is based on spectroscopy, the phenomenon in which white light separates into colored bands representing different electromagnetic energies. Because light functions as a wave, the color bands signify waves of varying length, frequency, and amplitude (height). For example, higher energy waves have shorter wavelengths, while lower energy waves have longer wavelengths [5]. The diagram below lays out the spectrum of electromagnetic energies, starting with low energy waves on the left and ending with short energy waves on the right [5, Fig.2]. Figure 2: Spectrum of Electromagnetic Energies Using these different energies, scientists can take measurements or make opaque materials more transparent to reveal details not visible to the naked eye. To accomplish these tasks, they use spectral imaging devices, which are more complex versions of the refracting instrument Newton used over four centuries ago [5, Fig.3]. Figure 3: Modern Spectral Imagining Device In Newton’s original model, sunlight enters through the window and passes through a prism, which reflects the color spectrum onto a screen. Though the technology has advanced, the basic process is essentially the same. The spectroscope’s lens gathers light reflected by the target object and directs it into the spectrograph, which contains either a prism or gate to disperse it into its component color bands / wavelengths. A sensor in the camera component then catches the dispersed light and produces a 2D image; to develop this into a 3D image, multiple images of the target are taken and layered to create a “datacube.” Researchers interpret this data by determining which elements of the target object they want to identify, then matching them with a specific color band or wavelength on the spectrum [1]. This data can also be graphed to track patterns or significant changes. For example, suppose a food manufacturer wants to test the quality of their fish sticks by measuring the fat and water content. Lab workers would focus the lens of the spectral imaging mechanism on sample fish sticks from the required batch, and bombard them with electromagnetic radiation. The spectrograph will disperse the reflected energy to the camera, which produces an image of the fish sticks with different colored regions to represent the elements the researchers want to assess (in this case, water and fat). The manufacturer can then use this data to make any necessary adjustments to the composition of the product. With the data collected, experts must now decide how to visualize and interpret it. This is no easy task, since spectrographs produce much larger, more complex files than a regular digital camera that can only be analyzed with specialized software. Preferred methods may vary by field and purpose—for example, a forensic scientist might want to identify the chemical composition of an accelerant used in an arson case, while geologists might search for mineral deposits by studying anomalies in spectral images of a piece of land. Some current methods for processing spectral data include similarity mapping, unmixing, and spectral estimation. Depending on the method they used, scientists then feed the collected data into specialized software such as Spectra Plus or Vernier Spectral Analysis to produce detailed graphs, maps, or other visuals. These images allow them to identify crucial patterns in the data. For example, in 2016, a group at MIT tested a prototype for a hyperspectral imaging camera that allowed them to view the contents of a book without even opening it. Using “tetrahertz radiation”, they produced images of letters by targeting specific pages [7, Fig. 5]. That same year, NASA used spectral analysis to study JR1, a Kuiper Belt object just beyond Pluto, with their New Horizons spacecraft; based on the light curve detected by New Horizon’s sensors, they created a graph tracking JR1’s rotational phases [8, Fig. 6]. Similarity ppin To create their images of individual pages and letters in the document, the MIT team used unmixing strategies to identify the unique properties of the paper material and ink, and highlight the specific elements they want to uncover. This type of non-invasive analysis makes it possible to read texts that are faded, smudged, or too fragile to physically handle. NASA, on the other hand, used similarity mapping to examine the characteristics and movements of JR1. Their scientists compared and contrasted hundreds of images from New Horizon and the Hubble Telescope to assess its magnitude and rotational phrases over the course of a year. By analyzing this data, they hope to uncover clues to the origins and significance of Kuiper Belt Objects in our solar system. Current Applications With applications in the fields of astronomy, geography, geology, medicine, archeology, and manufacturing, the uses for spectral imaging are myriad and varied: Determining the composition, temperature, or other physical properties of celestial bodies (i.e. stars, planets, asteroids) Locating and tracking atmospheric changes or anomalies Analyzing the chemical composition of pharmaceuticals to ensure quality and safety Detecting forgery, arson, or other crimes through analysis of inks, accelerants, and other materials Assessing the nutrition value and fat content of processed foods Identifying specific types of mineral deposits or oil pockets in a targeted region Surveying archeological sites to locate structures that are buried or not easily visible Potential / Developing Applications Throughout the last decade, though, the most intriguing research has focused on recovering lost or indecipherable cultural works, advancing nanotechnology, and improving medical testing. In 2012, for example, a team at the University of Pennsylvania used a spectral imaging device to decipher passages from the diary of famed 19th century explorer David Livingstone. Smudged and faded, only 15% of the text was previously readable [9]. More recently, a group at MIT tested a prototype for a hyperspectral imaging camera that allowed them to view the contents of a book without even opening it. They report that the device could distinguish specific letters “up to nine pages deep,” and theorize that the technique may prove useful in analyzing ancient texts that would be damaged by other, more invasive forms of testing [7]. While their peers use this technology to preserve delicate cultural artifacts and explore sources of renewable energy, scientists in the medical field hope they can use it to save lives. Recent studies have demonstrated strong potential for more refined use of spectral imaging in conducting retinal scans, identifying arterial plaque, and detecting cancerous growths in breast tissue [10]. These techniques could lead to earlier and more accurate detection of disease. They are also less invasive than other methods and do not require complex sample extraction, making them an attractive alternative for medical personnel and patients. Conclusion As spectral imaging equipment becomes more affordable and widely available, its possible uses in modern industry will continue to multiply. It allows researchers in fields as diverse as astronomy, geology, archeology, and manufacturing to more clearly distinguish subtle, sometimes invisible, details and patterns. Recent studies have also demonstrated strong potential for more refined use of spectral imaging in the medical field, such as conducting retinal scans, identifying arterial plaque, and detecting cancerous growths in breast tissue [8]. For further reading, please refer to sources listed on the Reference page. References
[1] Resonon. (n.d.). “What is spectral imaging and when should I use it?” Available: https://www.resonon.com/whitepapers/Resonon-Hyperspectral-Tutorial.pdf
[2] Chem Team. (27 February 2017). “Spectrum-Newton.” Available: http://www.chemteam.info/Electrons/Spectrum-History.html
[3] MIT. (2016). “The era of classical spectroscopy”. Available: http://web.mit.edu/spectroscopy/history/history-classical.html
[4] MIT. (2016). “The era of modern spectroscopy”. Available: http://web.mit.edu/spectroscopy/history/history-modern.html
[5] University of Arizona. (n.d.). “What is spectroscopy?” Available: http://loke.as.arizona.edu/~ckulesa/camp/spectroscopy_intro.html
[6] Y. Garini, I. Young, and G. McNamara. (3 March 2017). “Spectral Imaging: Principles
and Applications.” International Society for Analytical Cytology. Available:
http://semanticscholar.org/deb63/94631a09cb9f92838c41d767933f3f0143b6.pdf
[7] L. Hardesty. (26 February 2017). “Judging a Book Through Its Cover.” MIT News.
Available: http://news.mit.edu/2016/computational-imaging-method-reading-reads-closed-books-0909
[8] S. Porter. (27 February 2017). “New Horizons: Getting to Know a KBO.” NASA. Available:
http://blogs.nasa.gov/pluto/author/wkeeter/
[9] “ Tenacity, technology reveal Livingstone’s words.” (26 Feb. 2012). Pittsburgh Post-Gazette. LexisNexis.
[10] B.I. Grammatikov. (2014). “Modern technologies for retinal scanning and imaging.”
BioMedical Engineering OnLine, 13(1), 1-57. Academic Search Premier.
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