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2-D FIR filter using frequency sampling

designs a two-dimensional FIR filter with frequency response `h`

= fsamp2(`Hd`

)`Hd`

,
and returns the filter coefficients in matrix `h`

. The filter
`h`

has a frequency response that passes through points in
`Hd`

. `fsamp2`

designs two-dimensional FIR
filters based on a desired two-dimensional frequency response sampled at points on
the Cartesian plane.

produces an `h`

= fsamp2(`f1`

,`f2`

,`Hd`

,`[m n]`

)`m`

-by-`n`

FIR filter by matching the
filter response at the points in the vectors `f1`

and
`f2`

. The frequency vectors `f1`

and
`f2`

are in normalized frequency, where 1.0 corresponds to half
the sampling frequency, or π radians. The resulting filter fits the desired response
as closely as possible in the least squares sense. For best results, there must be
at least `m*n`

desired frequency points. `fsamp2`

issues a warning if you specify fewer than `m*n`

points.

`fsamp2`

computes the filter `h`

by taking the
inverse discrete Fourier transform of the desired frequency response. If the desired
frequency response is real and symmetric (zero phase), the resulting filter is also zero
phase.

[1] Lim, Jae S.,
*Two-Dimensional Signal and Image Processing*, Englewood
Cliffs, NJ, Prentice Hall, 1990, pp. 213-217.