An integral image lets you calculate summations over image subregions. Rapidly.These summations are useful in many applications, like calculating HAAR wavelets. These are used in face recognition and other similar algorithms.
Suppose an image is w pixels wide and h pixels high. Then the integral of this will be w+1 pixels wide and h+1 pixels high. The first row and column of the integral image are all zeros.
All other pixels have a value equal to the sum of all pixels before it.
See the integral in the above image? Every pixel is the summation of the pixels before it (above and to the left).
Now, to calculate the summation of the pixels in the black box, you take the corresponding box in the integral. You sum as follows: (Bottom right + top left - top right - bottom left).
So for the 3,5,4,1 box, the calculations would go like this: (30+0-17-0 = 13). For the 4,1 box, it would be (0+15-10-0 = 5).
This way, you can calculate summations in rectangular regions rapidly.
With the basic idea in mind, you can extend it to more types of summations. You can calculate the sum of squares. You can rotate the image by 45 degrees and then do the summations. Then, you can calculate the totals in any arbitrary rectangular region that is upright or tilted at 45 degrees.
You can calculate summations on irregular areas too (only those with 90 degree corners though). Not just that, you can do super fast blurs, approximate gradients and compute means and standard deviations very fast.
OpenCV comes with a predefined function to calculate an integral image.
void cvIntegral(const CvArr* image, CvArr* sum, CvArr* sqsum=NULL, CvArr* tilted_sum=NULL);
The parameters are, as always, self explanatory:
image
: the source imagesum
: the sum summation integral imagesqsum
: the square sum integral imagetiled_sum
: image is rotated by 45 degrees and then its integral is calculatedCalculating integral images is trivial. But they let you do more complex stuff (like blurring, HAAR wavelets, etc) super fast. And cvIntegral
in OpenCV calculates integral images for you.