Normalized 2-D cross-correlation

`C = normxcorr2(template, A)`

gpuarrayC = normxcorr2(gpuarrayTemplate,
gpuarrayA)

`C = normxcorr2(template, A)`

computes
the normalized cross-correlation of the matrices `template`

and `A`

.
The matrix `A`

must be larger than the matrix `template`

for
the normalization to be meaningful. The values of `template`

cannot
all be the same. The resulting matrix `C`

contains
the correlation coefficients, which can range in value from -1.0 to
1.0.

```
gpuarrayC = normxcorr2(gpuarrayTemplate,
gpuarrayA)
```

performs the normalized cross-correlation operation
on a GPU.

The input matrices `template`

and `A`

can
be numeric. The output matrix `C`

is `double`

.

The input matrices `gpuarrayTemplate`

and `gpuarrayA`

are
gpuArrays whose underlying type must be numeric. The output matrix `gpuarrayC`

is
a gpuArray whose underlying class must be `double`

.

[2] Haralick, Robert M., and Linda G. Shapiro, *Computer
and Robot Vision*, Volume II, Addison-Wesley, 1992, pp.
316-317.

Was this topic helpful?