Best strategy for preprocessing experiments with limited compute (U-Net, U-Net++, DeepLabV3)?

Hi, I’m working on an image segmentation project using U-Net, U-Net++ and DeepLabV3 with around 1000 images. I want to try different preprocessing methods like CLAHE, histogram equalization, unsharp masking and bilateral filtering, but I have limited GPU time. Is it okay to train with fewer epochs, like around 20 with early stopping, just to compare the preprocessing methods, then train longer later on the best ones? Will that still g