Filters in subsequent layers

So I recently started learning about CNNs, and one question struck out to menthe filters used in the second layer are a combination of the filters used in the first layer, right?

Lets say I make use of 4 filters in my first layer, and my second layer, I decide to combine any two, to give one filter, does this mean that during training, all I need to learn are the low level features, and it'll be propagated to the higher level ones, since its a combination of the lower level ones?

To further explain my point, suppose I have two 2D filter in the first layer of 3x3, this would mean I have 18 weights to learn in total, as the higher filters are simply combinations of the lower ones