I'm iterating over a 3 dimensional array (which is an image with 3 values for each pixel) to apply a 3x3 filter to each pixel as follows:
//For each value on the image
for (i=0;i<3*width*height;i++){
//For each filter value
for (j=0;j<9;j++){
if (notOutsideEdgesCondition){
*(**(outArray)+i)+= *(**(pixelArray)+i-1+(j%3)) * (*(filter+j));
}
}
}
I'm using pointer arithmetic because if I used array notation I'd have 4 loops and I'm trying to have the least p开发者_Python百科ossible number of loops. My problem is my notOutsideEdgesCondition
is getting quite out of hands because I have to consider 8 border cases. I have the following handled conditions
- Left Column:
((i%width)==0) && (j%3==0)
- Right Column:
((i-1)%width ==0) && (i>1) && (j%3==2)
- Upper Row:
(i<width) && (j<2)
- Lower Row:
(i>(width*height-width)) && (j>5)
and still have to consider the 4 corner cases which will have longer expressions. At this point I've stopped and asked myself if this is the best way to go because If I have a 5 line long conditional evaluation it'll not only be truly painful to debug but will slow the inner loop. That's why I come to you to ask if there's a known algorithm to handle this cases or if there's a better approach for my problem. Thanks a lot.
Yes, there's a much better way. Write a fast loop to handle the cases where there is guaranteed to be no boundary problems. This will consist of the region from the second to the next-to-last columns and the second to next-to-last rows. Then you can write four routines to handle each of the sides (row 0, column 0, row N and column N) and you can hand code the last four points.
That said, there are also a heck of a lot faster ways of doing the addressing calculations you're doing.
A nice tip is to add an additional row at the top of the array, and another at the end (do the same for the columns).
These additionals rows/columns won't contain any information but they will ease the computation (no border cases). At the price of consuming more memory...
Just an idea :)
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