**4. Image visualization**

Various chart options in Microsoft Excel can be used to visualize the image data once the data are available in Excel. With the desired dataset selected, the appropriate chart option can be accessed via the INSERT Ribbon. [16, 17] identified the 3D surface and contour as the preferred or effective depictions of the two-dimensional image data of the R, G, and B bands and further processed data. Both charts have a spatial dimension of 255 categories on the x-axis and 255 data series on the y-axis, and a spectral dimension of 256 pixel values (i.e. 0–255

gray levels) on the z-axis for the 3D surface chart. The pixel values (signal intensities) are displayed as different colors in the contour chart. However, in order to reduce the dimensionality of the data and the complexity of image processing, the 256 pixel values are displayed in only a few colors. However, once features in the image have been identified, the data can be further processed to reduce its dimensionality.

The one-dimensional datasets of the R, G, and B band which are shown in the UC worksheet in Excel and their derived datasets can be visualized in two ways. First, histograms of each dataset can be obtained utilizing the Data Analysis ToolPak. The Data Analysis ToolPak is an optional add-in tool in Excel. Second, similarly as described in the preceding paragraph, the X Y (scatter) chart can be accessed to produce cluster plots of any two datasets (columns). This can be useful for feature extraction and unsupervised classification purposes.

**Figure 3** shows 3D surface charts, contour charts, and histograms (rows 1, 2, and 3, respectively) of R, G, and B band data (columns 1, 2, and 3, respectively) from **Figure 1a**. The 3D surface and contour charts were set to display only six colors with the data range. These charts show variations in the skin condition, however, the features are not very well separated. Also, as expected, the nature of the data is clearly different among the three bands due to differences in signal responses of different features.

#### **Figure 3.**

*Various visualizations of R, G, and B data: columns (a = R data; b = G data; and c = B data) and rows (1 = 3D surface; 2 = contour chart; and 3 = histogram).*
