This page collects a range of processing techniques and how to implement them in practice. Some of these recipes are my own, some have been developed by the community (particularly at the UMSF forums, and others have been repurposed from professional scientific processing.
Before tackling any of the tutorials listed here, I highly recommend familiarizing yourself with Emily Lakdawalla's introductory series on space image processing. This series covers the basic concepts of finding data, converting it to formats usable in photo editing software, and creating color images.
Here is my brief introductory guide to the concept of color, how spacecraft understand it, and my vocabulary regarding color terms. It should provide a good foundation to understanding the data you'll be working with and why getting natural-looking images from data can often be difficult. Here are a few tutorials for working with color data:
Image differencing (or ratioing) is a technique to isolate and enhance subtle details within an image. The basic principle of image differencing is relatively straightforward, but can be implemented in very different ways depending on the goal of the processing. Here are a few tutorials that walk through these implementations:
Deconvolution is a technique to recover sharpness lost by motion smearing or optical quality of a camera lens. Here is an introductory tutorial describing how to implement it with ImageJ. This is a great general purpose technique, especially for spacecraft using analog cameras.