I recently got interested in ML algorithms that alter or augment existing images. I was intrigued by the opportunities that these algorithms can expand our existing perception of the world.
What first got into my mind was ultrasound photograph of the fetus. This is an image that is limited to be seen in black and white. How would it feel different if we are able to see this in color? Unfortunately, since there is no ground truth for this image yet, the colorization wouldn’t work for this. However, it revealed how there are things that we desire to see in color.
Another idea came to mind, which is to colorize images of subjects that no longer exist, such as extinct animals. Following is my first attempt at colorizing a photograph of a Tasmanian tiger, which went extinct around 1936:
Then I questioned how the use of color influences our perception and decisions. How would colorization of existing images hint novel insights that wouldn’t have been noticed otherwise? I recognized how colors used in political campaigns were obscured in black and white photographs whereas the use of red and blue today is very explicit in these campaigns. It triggered my curiosity for how these photographs would appear differently when they are in color. I scraped images of U.S. presidential election campaigns from 1952-1980 at Getty Images collection and ran the colorization script.
While some images worked better than the other, the effect that colors contribute to the portrayal of election campaigns was stark. I made a chart to see if there were any patterns or trends.
I think it would be also interesting to arrange these charts based on other variables such as candidates or parties. It would have been also better if I had a larger collection of images of election campaigns, which I could have used a training set to get better results.