Can I use an ANN to translate image output from one sensor to simulate output from another sensor? Say, for instance, if I had image data from one high resolution digital camera and wanted to make it look like it was taken from another, lower resolution, digital camera?  Would training input/output pairs of overlapping images be a good way to do this?  What is this technique called?

For example, say I wanted to be able to count benches in parks in LOW resolution imagery.  Could I go through these sample images and create an appropriate dataset of high and low resolution pairs to train a network to learn what a low resolution bench looked like?  Would I be able to discern low resolution benches if my training set was incredibly diverse (image chips if entire city parks vs individual objects like fountains, trees and statues)?





I like this example because the images come from different sensors as well as being different resolutions. Some of my research has led me to super resolution, which is kind of the opposite of what I'm trying to do.

As for the amount of data, it would be painstaking but not technically difficult to get overlapping high and low resolution imagery.
This is very much possible. There is a function which can map the images from the higher resolution pictures to the lower dimensional ones; and a neural network can be trained to learn that function. 

However, to train a neural network to do this you will need thousands of images from both cameras. Then you can feed the pictures taken with your higher resolution camera as the input to the network and then compute the loss of the network at the output with the corresponding lower resolution images. 

If you do not have so many images, there has been work on taking images and applying some sort of filter to change their appearance. These techniques are often called style transfer, you can find some tutorial here and code which I have tried and can confirm works here. It might be hard to get a representative image to use as the style image using your old camera. You can try an average of a few pictures, or a picture of a white background, you would have to try things out, I do not know what would work in this case.

If you share examples of your data we can help you more.