It wouldn’t increase the regularization, but would decrease the model capacity.
Dropout can also be seen as a method to decrease the model capacity during training, as each training iteration will use a new and “smaller” model than the original one.
I would nevertheless try to increase the regularization first (dropout and data augmentation), before using a smaller model.