Chapter 10. Parallel Processing
In this chapter, we will take another step in code optimization; we will experiment with the possibility of using multiple processor cores to perform calculations.
Using the satellite images from the previous chapter, we will use Python's multiprocessing library to distribute tasks and make them run in parallel. As an example, we will experiment with different techniques to produce true color compositions from Landsat 8 data, with better resolution and a greater level of detail.
To achieve our objects, we will go through these topics:
How multiprocessing works
How to iterate through two-dimensional image blocks
Image resizing and resampling
Parallel processing in image operations
Image pan sharpening
