How sparsity connection helps to reduced the total number of parameter

Course Q&A Deep Learning Specialization Convolutional Neural Networks
1

Dear mentor! we have seen different variants that CNN is working better because they reduced the number of parameters. One reason is " Sparsity connection "

First of all that what i understand from sparsity connection is that ( the pixel at the next layer is not connected to all input image means only local group is connected to that pixel or if i say like it is not trying to get information from the full image every time )

but how sparsity connection is reduces the number of total parameters .

2

The reduction in the number of parameters comes from the fact that the filter is used repeatedly across the image, rather than having coefficients that are unique to each position in the input. I’m not sure how that maps to the normal sense in which people use the term “sparsity” though …