Introduction - If you have any usage issues, please Google them yourself
Gaussian filtering in one, two or three dimensions is among
the most commonly needed tasks in signal and image processing.
Finite impulse response filters in the time domain
with Gaussian masks are easy to implement in either floating
or fixed point arithmetic, because Gaussian kernels are
strictly positive and bounded. But these implementations are
slow for large images or kernels. With the recursive IIRfilters
and FFT-based methods, there are at least two alternative
methods to perform Gaussian filtering in a faster way,
but so far they are only applicable when floating-point hardware
is available. In this paper, a fixed-point implementation
of recursive Gaussian filtering is discussed and applied
to isotropic and anisotropic image filtering by making use of
a non-orthogonal separation scheme of the Gaussian filter.