Preprocessing for finetuned CNN model from pretrained models
If a network was trained let's say on centered input values (i.e. ranging from -1 to 1) with subtracted mean channel values computed on the ImageNet, it is desirable to keep this preprocessing to make fine-tuning easier. 

From other hand, CNN sometimes can be surprisingly robust to this kind of input fluctuations and, unless you freeze the pre-trained part, can adapt to the changes in the input. So, if you just change mean channel values from default [103.939, 116.779, 123.68] to [128, 128, 128] this should work ok. Otherwise, just compare how the accuracy is improving during fine-tuning using the vgg16 preprocessing and your method.