Specifications

Intel
®
Image Processing Library Reference Manual
6-4
6
In addition, iplConvolveSep2D(), a convolution function that uses
separable kernels, is also provided. It works with convolution kernels that
are separable into the x and y components.
Before performing a convolution, you should create the convolution kernel
and be able to access the kernel attributes. You can do this using
the functions
iplCreateConvKernel(), iplGetConvKernel(),
iplCreateConvKernelFP() and iplGetConvKernelFP().
In release 2.0, the function
iplFixedFilter() function has been added to
the library. It allows you to convolve images with a number of commonly
used kernels that correspond to Gaussian, Laplacian, highpass, and gradient
filtering.
Also, for compatibility with previous releases, the functions
iplCreateConvKernelChar() and iplGetConvKernelChar() have
been added. They use 1-byte
char kernel values, as opposed to integer
kernel values in
iplCreateConvKernel() and iplGetConvKernel() .