The Effect of a Kernel on an Image By Filtering I am going through an old exam paper and trying to understand this question where they ask us to tell them what effect the following image filter would have if its convolved with an image:

     0     0     0     0     1     0     0
     0     0     0     0     0     0     0
     0     0     0     0     0     0     0
     0     0     0     0     0     0     0
     0     0     0     0     0     0     1
     0     0     0     0     0     0     0
     1     0     0     0     0     0     0


Now by using Matlab I can easily tell that this blurs the image. But what I am wondering is how would one know by just looking at this filter that the image will get blurred when this filter is applied?

Here's the image I'm working with in its original form:



Here's the same image after being convolved with the kernel in Matlab:



I would appreciate an explanation here or if someone can point me in the right direction as to a reading online I'd appreciate that too.
Convolution with following kernel returns the signal unchanged.

 0     0     0     0     0     0     0
 0     0     0     0     0     0     0
 0     0     0     0     0     0     0
 0     0     0     1     0     0     0
 0     0     0     0     0     0     0
 0     0     0     0     0     0     0
 0     0     0     0     0     0     0


If the '1' is shifted to the right one position, the convolution output will be shifted to the right one position as well.

If the '1' is a '2' the convolution output will be double (scaled by 2).

If there is more than one non-zero number in the kernel, the convolution output will be the addition of each scaled and shifted copy.

For your kernel

 0     0     0     0     1     0     0
 0     0     0     0     0     0     0
 0     0     0     0     0     0     0
 0     0     0     0     0     0     0
 0     0     0     0     0     0     1
 0     0     0     0     0     0     0
 1     0     0     0     0     0     0


the output is the addition of three copies of the signal, shifted by (1,3), (3,-1) and (-3,-3) and scaled by 1. I wouldn't call it blurring though.