What knowledge should I gain for developing a supervised image processing software that learns how to edit photos based on past behavior? I have done several machine learning projects but all of them have been connected to the traditional machine learning (predictions, classifications, etc.). I have currently been offered a project to finish in less than 6 months.

The idea is to develop/improve a pre-existing software. The software takes the image of a molecule from an advanced molecule and then tries to highlight the cell line with red, some times the software takes the background or the lines of other cells also as the highlighted part, and thus the user has to manually edit and trim such mistakes. The idea is to make the software learn from user's edits and behavior over time.

One thing I want to know is whether such a 6-month project is realistic for someone with no background in image processing and pattern recognition? Or is it going to be terribly difficult because I only have had experience with "data-oriented"/statistical machine learning?

My other question is; what type of concepts/topics should I dig deep into to learn the fundamentals of carrying out this project?
From the description of your problem, you need both Computer Vision and Deep Learning for a task like that. It is going to be extremely difficult, but you are more in advantage than anyone else, given you have a strong statistical and machine learning background. You don't have to worry a lot about the image processing part as there are libraries that will do that for you. You can look into PIL for that.The hard part is the learning from the edits part.A simpler way to solve this problem would be to focus on image processing and pick out the cell line clearly. The other way would be to train a Convnet on a large collection of 'labelled-images' of the cell-line, so that it is able to identify it in any picture. I do think it is quite a hard problem to solve but do give it a try. Cheers. All the best.