Enhancement of old colour photographs using Generative Adversarial Networks

It’s almost Christmas, I haven’t posted anything in a while and I see that WordPress has an Image Compare feature, so let’s have some colourful fun. When I’m not at the computer writing R code, I can often be found at the computer processing photographs. Or at the computer browsing Twitter, which is how I came across Stuart Humphryes, a digital artist who enhances autochromes. Autochromes are early colour photographs, generated using a process patented by the Lumière brothers in 1903. You can find and download many examples of them online. Stuart uses a variety of software tools to clean, enhance and balance the colours, resulting in bright vivid images that often have a contemporary feel, whilst at the same time retaining the somewhat “dreamy” quality of the original. Having read that one of his tools uses neural networks, I was keen to discover how easy it is to achieve something similar using freely-available software found online. The answer is “quite easy” – although achieving results as good as Stuart’s is somewhat more difficult. Here’s how I went about it. First, head over to Github and install Real-ESRGAN. It’s a suite of software, written in Python, that uses a type of neural network called a GAN (Generative Adversarial Network) for image processing. As much as I know about GANs can be found at the Wikipedia link so this is a practical, rather than a theoretical guide. You can i...
Source: What You're Doing Is Rather Desperate - Category: Bioinformatics Authors: Tags: multimedia enhancement gan image photography processing python Source Type: blogs