## 3 Results and Discussion
### Practical Aspects of Detection  
Data acquisition parameters for this study were selected to allow comparison of relative responses across all wavelengths of a given hyperspectral data set and not to optimize acquisition parameters for detection at any particular wavelength. In this regard, for reflectance imaging, exposure time was maximized and aperture was adjusted to eliminate saturation at the worst-case wavelength across the acquired spectrum. Furthermore, the aperture correction was crude as it was done visually and not by image analysis. The stated conclusion of this study was that detection of bird excrements could be accomplished using any of the large range of wavelengths and suggested the use of 525 nm. However, the acquisition protocol resulted in images at 525 nm that were inconsistent in intensity across hyperspectral image sets. To address this inconsistency, the 525-nm images were normalized based on intensity histograms. An alternate method commonly used to normalize the effects of differences in illumination intensity is to use a ratio of images acquired at two different wavelengths. However, ratio calculations would require additional computations and it was likely, given the dramatic differences in relative spectral responses seen in this study, that normalization would not be necessary if image acquisition parameters were optimized for 525-nm images and for actual ambient illumination. Another problem that was encountered related to the color of some of the ribs of roanine leaves. Presumably due to lack of exposure to the sun, the problem ribs had little pigmentation. In commercial fields prior to harvest, the problem ribs would not have been visible. The problem rib areas were masked-out prior to detection. Using this detection scheme, bird droppings for all of the nine hyperspectral data sets selected for in-depth analyses were detectable using a fixed threshold of 3000. There were no false positives. For fluorescence detection, using the raw images, 100% of bird droppings could be detected at 525 nm using a threshold of 250 with no false positives. These examples are not meant to suggest use of a specific detection scheme, but only to emphasize the robustness of the ability to detect bird droppings using imaging techniques. For both reflectance and fluorescence imaging, because of the ease of differentiating bird droppings from the background matrix across a wide range of wavelengths, selection of the most appropriate wavelength and bandwidth for imaging will depend more on equipment considerations and less on the actual wavelength used for detection. Critical consideration would involve questions such as the cost of components verses overall sensitivity. The least expensive components that might be used include a monochrome camera and a single-wavelength interference filter. Cost considerations for the camera would revolve around factors such as sensitivity, noise, resolution, weight, and dynamic range. A high resolution camera might be able to detect small bird droppings such as those seen for mourning doves. For the filter, there are generally two types of interference filters. The less expensive filters have a bell-shaped transmittance distribution across wavelengths. These filters are described in terms of the center frequency and a pass-band where the edges of the pass-band are the wavelengths where the transmission is half the maximum at the center (FHHM, full height at half max). The downsides of this type of filter are that significant light is transmitted at wavelengths outside the pass-band, and the transmittance at the center wavelength can be low (commonly less than 50% in the blue-green region). The more expensive filters have a pulse-shaped transmittance distribution with sharp edges and a flat top. The advantages of this type of filter are that little light is transmitted outside the pass-band, and that the transmittance across the pass-band approaches 100%. The disadvantage is cost. The final selection of equipment will also depend on implementation.