Intel® Integrated Performance Primitives

Manipulate srcStep to do Median Filtering along diagonals?

Image Median of a large neighborhood can be approximated well (and much faster) by computing the median of medians using line medians.
In that context I wish to compute the median along diagonals (i.e. neither rows nor columns), but IPP does not seem to support this?
Would it be possible to accomplish this by computing a median with a column mask(1x3 or 1x5) on an image where the srcStep is artificially increased or decreased by an amount corresponding to the storage required for one pixel?

IPP cryptography performance problem


      I'm using IPP cryptography API  to develop program! do you have any documents about   optimization cryptography API  performace comparing with not  optimization cryptography  algorithem?

     Because ,when I was testing the RSA algorithem , I find the intel IPP RSA  algorithem performance wasn't well with openssl sorce code! If you have any testing report or document abot  cryptography algorithem optimization compare with not optimization ,can you send to me ? thank you!

Incorrect min/max size IPPIMinMax and IPPsMinMax

I have observation with respect to computing min and max value of image pixels using IPPiMin/Max fucntion.i am getting in correct result.

i have also tried with ippsMinMax16u. the function is working well with small array size i.e. (4000*12380) Ipp16u. but for bigger size like

(4000*387644) Ipp16u array, function is not working giving zero as value.

i am running with IPP version (2017 update 2)

kindly suggest me the solution i will be thank full to you.

IPP FFT application on AMD


I am working on an application that uses the FFT of IPP.

It needs to run on Intel as well as on AMD processors.

I am not asking for an optimized performance. I am simply interested whether my "ready to deploy" application will run on either systems.

I browsed the forum a little, but could not find a suitable answer.

Thank you in advance

Best regards


FilterWiener documentation


I am refering to where is described how Wiener Filter is computed using local mean and variance.
I wonder if final computation: Y(i,j) = m(i,j) + (s(i,j)^2-v) / s(i,j)^2 * [X(i,j) - m(i,j)] is there correctly described ?
And what happens if s(i,j) = 0 as there is division by zero ?

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