Process Hyperspectral data in Python
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Project Budget$30 - $250 USD
A simple program, written in Python, to run on a Linux server.
The nature of the data is hyperspectral cubes, which are stacks of images (3D cubes). The main purpose of this program is to perform the operation of reflectance correction in these cubes (very simple linear algebra) and store the processed data. Also, this operation has to run in parallel for multiple cubes, for efficiency.
So, briefly, the program
- Accesses multiple subdirectories of a main, given, root directory
- For each directory
o Reads all files in a directory
o Finds the files that are named ‘white’ and ‘dark’
o Performs the reflectance correction operation (the formula will be given) using the white, dark and raw files that are in the folder
o Stores the processed data in a new directory
- Run in parallel for many subdirectories
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