I know that these days' style-transfer GANs should be able to style-transfer day images into night images. I however prefer to do it using a set of elementary image processing manipulations, so I can control their random parameter ranges.
I have a small dataset of images taken at night, which are very hard to train on with transfer-learning from an ImageNet pre-trained network. This is kind of making sense, as ImageNet images are usually taken in daylight conditions.
I therefore want to try to create a "night version" of ImageNet, by applying elementary image-processing manipulations on it (e.g., adding noise, shrinking the color histogram and reducing its mean, etc.). That way, I hope I will be able to train a network that will be useful for transfer-learning on night images.
Are there known algorithms/methods for doing that daylight->night conversion using image processing?