Tyler John Nigon, University of Minnesota, Minneapolis, MN
Aerial multispectral imagery can provide valuable information for precision agriculture applications, can aid in agricultural decision-making, and provide powerful research information. However, it is often necessary to perform some level of data cleaning and image preprocessing before the data are quantitatively objective and useful for research purposes. The Tetracam Micro-Multiple Camera Array (MCA) System is a popular multispectral imager, but there are preprocessing issues that are not adequately addressed using Tetracam’s included software application (i.e., PixelWrench2). Prior to using this package, RAW images must first be converted to multipage TIFs using PixelWrench2 because of the proprietary format of Tetracam’s RAW image files. TetraPy has the following preprocessing functionality for all multipage TIFs in the input directory (i.e., images are batch processed): i) converts images from 8-bit to 10-bit pixel depth if images were captured using the 10-bit RAW setting, ii) writes all metadata to an independent header file (i.e., .hdr) according to ENVI standards, iii) uses user-input geolocation and the image timestamp to calculate and record solar zenith and azimuth to the header, iv) performs image color balancing due to multiangular sensing (dependent on Py6S), v) allows user to export images to .dat data format as band interleaved by line, band interleaved by pixel, or band sequential, and vi) has some functions to aid in improving band co-registration. TetraPy greatly reduces the time that Tetracam users spend in preprocessing their imagery while maintaining data integrity and original image metadata. TetraPy is licensed under the GNU General Public License.