We regard the output of a convolution layer as an 'image' so that the output of each computation unit is considered to be a 'pixel' of m channels where m is the number of weight vectors (i.e., the number of rows of W) or the number of neurons.
a convolution layer converts image regions to m-dim vectors, and the locations of the regions are inherited through this conversion.