## 4 Derived Products and Data Processing
### Digital Image Enhancement with DStretch  
To preserve the highest possible quality in the enhanced output mosaic of orthorectified images, a strategy similar to those proposed by [PERSON] and [PERSON] [29] for applying DStretch on Gigapixel images has been followed. In this case, it has been preferred to first apply the decorrelation algorithm on every single picture (Figure 3) and then compose the mosaic.  
We have worked with the plug-in DStretch Version 8.22. The procedure begins with a representative area selection on the image of the piece (orthophotomosaic of Figure 1), the definition of the intensity scale and the choice of the color space with which the decorrelation algorithm manages to emphasize the areas of interest. In most cases, it is necessary to select several color spaces to highlight different aspects. The color space used to emphasize the red paint is LRE (Figures 5g and 9). Additionally, good results have been obtained to isolate traces recorded with the DStretch-YRE enhancement (Figure 5h). The different classified images are saved in TIF format together with their corresponding matrix file (.txt) with information on the transformation carried out. This file will be used later andcontains the chosen color space, the 9 coefficients of the covariance matrix, and the mean color value of the image selection.  
Figure 8: Head detail resulting from superimposing the hillshade layer with a transparency of 35% on the high pass layer. Nine outlines of the lines are shown on the horsehair (**A–C**), ears (**D**), forehead (**E**), snout (**F**), jaw (**G**,**H**), and neck (**I**).  
The next step begins with the selection of the necessary images to compose the mosaic ensuring a suitable coating. In this case, only 16 images were selected (Figure 3). The same DStretch enhancements were applied on all images, importing the file with the matrix data and using the mean color value stored there. The treated images were replaced in the Agisoft project by the original raw ones. The last step was the creation of the mosaic using only the selected images and with the same parameters (pixel size, projection plane, etc.) used in Section 4. Figure 9 shows the result of superimposing the hillshade layer with a 60% transparency on the DStretch-LRE orthophotomosaic layer.  
Apart from the pigment, DStretch allows documenting other aspects related to the state of the artifact conservation at the time of photo grammetric acquisition. In Figure 5i, a DStretch-YBG enhancement is applied that shows damaged areas due to different causes or reasons. Dark green shows  
Figure 9: Plaquette 16330A, the result of superimposing the hillshade layer with a transparency of 60% on the DStretch-LRE orthophotomosaic layer.  
areas with dirt due to biodeterioration and white areas that have suffered a recent patina (and pigment) loss as a result of bumps, scratches, etc. This last aspect is also very well reflected using the DStretch-LYE enhancement (Figure 5j).  
The last step is to create a mask to extract the areas of interest, using DStretch's Hue Mask Panel tool, found within Expert mode. Figure 5k shows the pigment masked from the DStretch-LRE enhancement, while Figure 5l shows the overlapping of the hillshade layer with a transparency of 50% on the layer with the pigment, which in turn, overlaps on the high pass layer. This triple superposition will allow us to study in detail the relationship between the painted surface and the horse figure outline engraving.