Image acquisition techniques

Digital images are created to represent the real world (Burger & Burge, 2016). Assuming rectangular images, they can be treated as matrices where each cell (i.e. pixel) contains information of the colour, and the rows and columns denote the perceived spatial dimensions of the imaged object(s). Therefore, the image resolution is represented by the number of measurements per elements in the real world (Burger & Burge, 2016). Pixels per inch (PPI) is an example of quantifying the resolution.

8 The pixel values are typically binary with length k, implying that a cell can represent 2^k different numbers. For example, an 8-bit grayscale image has k = 8, hence there are 2⁸ = 256 possible pixel values. The values are in the range 0, 1, 2, …, 255, each representing a grayscale intensity where the maximum brightness (i.e. white) is 255 and minimum (i.e. black) is 0. Figure 3 illustrates how a grayscale image is composed of many intensity values. For colour images, additional matrices are created; one matrix of intensity values for each colour. For example, an RGB-image would consist of three matrices, representing the colours red, green, and blue (Burger & Burge, 2016).

Figure 3: Illustration of how a grayscale image is composed of pixels; cells containing intensity values in a matrix. Image object (left) obtained using paid subscription from https://lucid.app/.

2.2.1. Scanning Electron Microscope (SEM)

Scanning electron microscopy is one of the established techniques in nuclear forensics and used for physical characterisation, as seen in Table 1. SEM can magnify an object up to 2,000,000 times (nature research CUSTOM MEDIA and Hitachi High-Technologies, u.d.) revealing intricated details of the structure of the objects. SEM provides the possibility to study the morphology and microstructure of the substance surface, and is therefore used to study UOCs (Mayer, Wallenius,

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& Fanghänel, Nuclear forensic science-From cradle to maturity, 2007) (Varga, Wallenius, Mayer,

& Meppen, 2011) (Keegan & al., 2014) amongst other things.

The working principle of SEM is to focus and direct the beam of high energy electrons into the specimen and record returning electrons to reconstruct an image. The essential SEM components are presented in Figure 4. The thermionic cathode releases electrons when heated up by an electric current. The electrons are accelerated towards the anode due to a strong electric field between cathode and anode. The electrons, called primary electrons, will form a broad diverging beam from the anode to the specimen if left unchanged. The electromagnetic lens focuses the beam, and electromagnetic deflectors direct the focal point. The incident beam hits the specimen surface and penetrates up to a depth of 1 μm (Khursheed, 2011). The primary electrons collide with the specimen’s atoms at different depths and scatter, where some will escape the surface. Primary electrons that collide with specimen atoms at the top surface undergo an inelastic interaction and result in secondary electrons being emitted. The secondary electrons provide information about the surface structure. Primary electrons colliding deeper within the specimen undergo elastic interaction and result in backscatter electrons. The secondary electrons are recorded by a detector and used to build a reconstructed image. The electromagnetic deflectors position the focal point to the top left focal point, and the number of secondary electrons is recorded. This gives the top-left pixel of the resulting image. The scanning process proceeds by scanning all pixels left to right in the first line before it shifts down to the second line repeating the procedure. A focal point with many recorded secondary electrons results in a bright pixel. Fewer recorded secondary electrons result in a dim grey pixel, while no recorded secondary electrons result in a black pixel.

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Figure 4: Schematic illustration of Scanning Electron Microscope. Illustration by author.

2.2.2. Hyperspectral imaging (HSI)

The concept of hyperspectral imaging (HSI) is to acquire an image at hundreds of continuous narrow bands in a region of the electromagnetic spectrum (Manolakis, Lockwood, & Cooley, 2016). Many different regions in the electromagnetic spectrum can be used, such as ultraviolet (UV), visible (Vis), and near infrared (NIR) (Amigo, Babamoradi, & Elcoroaristizabal, 2015) (Edelman, Gaston, van Leeuwen, Cullen, & Aalders, 2012). The imaging captures the interaction of incident light on the sample object (Edelman, Gaston, van Leeuwen, Cullen, & Aalders, 2012).

Various interactions are possible, and these are illustrated in Figure 5. One of them is the absorption of light in the material and eventually re-emission of the energy as radiation. Absorption is wavelength depended due to the intrinsic properties of the chemical composition of the material (Edelman, Gaston, van Leeuwen, Cullen, & Aalders, 2012).

The hyperspectral image consists of many image matrices, together as a stack, and these compose what is commonly named as a hypercube. Figure 6 illustrates this. As for a grayscale image, the spatial dimensions are the rows and columns in each image matrix, but the third dimension represents the wavelength  or wavelength band at which the image matrix was captured. The wavelength or band denotes the colour for which the corresponding image matrix contains

11 intensity values. For each pixel, a spectrum is acquired. The hyperspectral image can thus be represented as a three-dimensional dataset with the number of values equalling the number of rows times the number of columns times the number of bands. There are typically three ways of sampling information for building a hypercube (Manolakis, Lockwood, & Cooley, 2016); pixel-line scanning (pushbroom scanning), pixel by pixel scanning (whiskbroom scanning), and scanning by staring whilst changing wavelength filters.

HSI was primarily used in remote sensing from the start. Since then, the technique has been applied in e.g. pharmaceuticals, medical diagnostics (Edelman, Gaston, van Leeuwen, Cullen, & Aalders, 2012), food sciences, and other fields of research as well as production (Amigo, Babamoradi, &

Elcoroaristizabal, 2015). Even more interestingly, HSI has been applied in forensic sciences as it is a non-destructive and non-contact technique (Edelman, Gaston, van Leeuwen, Cullen, &

Aalders, 2012). Furthermore, the speed of acquisition, interpretability of both spatial and spectral information, as well as being portable, makes it very usable at the scene of investigation (Edelman, Gaston, van Leeuwen, Cullen, & Aalders, 2012).

Figure 5: Illustration of the different interactions light can have with a material; a) specular reflection, b) diffuse reflection by elastic scattering, c) emitted Raman shifted light by inelastic scattering, d) absorption, and e) photoluminescence emission by absorption. Inspired by (Edelman, Gaston, van Leeuwen, Cullen, & Aalders, 2012).

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Figure 6: Illustration of a hyperspectral image as a hypercube. Horizontal and vertical axes represent the spatial dimensions, and the depth denote different wavelengths . For each pixel, a spectrum has been acquired.