Not if all the additional input values are zeroes...doesn't matter whether you call it interleaving or padding or whatever. How does the filter accept more data inputs if you're simply feeding it more zeroes?
Jonathan, linear convolution increases the size of the output filter based upon the lengths of the convolved input arrays. It is basic DSP. That is how it accepts "more inputs" when convolved with incoming data.
I wrote a small program quickly for you to ascertain what I am saying. I shall double check for bugs as I was in a hurry, but the output produced is pretty satisfactory. I can provide the program to you or anybody else if requested.
After providing a random array of 128x128 as an input image and a normalized filter of 16x16, which coefficients were again random, the following results were gotten for the corresponding decimation factors (D):
Here error is the difference between cascaded convolution and "larger" convolution.
error = 1.7823e-12 (D = 2)
error = 6.0269e-13 (D = 4)
error = 6.9421e-13 (D = 5)
error = 8.4018e-14 (D =
The above errors are almost zero. The following is a detailed output for a decimation factor of D = 11.
Cascaded-two convolutions:
0.14434 -3.23658 2.43976
3.07258 3.39879 8.39013
-2.39454 -30.46508 -1.78851
Single "larger" convolution:
0.14434 -3.23658 2.43976
3.07258 3.39879 8.39013
-2.39454 -30.46508 -1.78851
error = 3.8223e-14 (D = 11)