laplace — Calculate the Laplace operator by using finite differences.
laplace(Image : ImageLaplace : ResultType, MaskSize, FilterMask : )
laplace filters the input images Image using a
Laplace operator. Depending on the parameter FilterMask
the following approximations of the Laplace operator are used:
1 1 -4 1 1
1 1 1 1 -8 1 1 1 1
10 22 10 22 -128 22 10 22 10
For the three filter masks the following normalizations of the resulting gray values is applied, (i.e., by dividing the result by the given divisor): 'n_4' normalization by 1, 'n_8', normalization by 2 and for 'n_8_isotropic' normalization by 32.
For a Laplace operator with size 3x3, the
corresponding filter is applied directly, while for larger filter
sizes the input image is first smoothed using a Gaussian
filter (see gauss_image) or a binomial filter (see
binomial_filter) of size MaskSize-2. The Gaussian
filter is selected for the above values of ResultType.
Here, MaskSize = 5, 7, 9, 11, or 13 must be used. The
binomial filter is selected by appending '_binomial' to the
above values of ResultType. Here, MaskSize can be
selected between 5 and 39. Furthermore, it is possible to select
different amounts of smoothing for the column and row direction by
passing two values in MaskSize. Here, the first value of
MaskSize corresponds to the mask width (smoothing in the
column direction), while the second value corresponds to the mask
height (smoothing in the row direction) of the binomial filter.
Therefore,
laplace(O:R:'absolute',MaskSize,N:)
for MaskSize > 3 is equivalent to
gauss_image(O:G:MaskSize-2:) >
laplace(G:R:'absolute',3,N:).
and
laplace(O:R:'absolute_binomial',MaskSize,N:)
is equivalent to
binomial_filter(O:B:MaskSize-2,MaskSize-2:) >
laplace(B:R:'absolute',3,N:).
laplace either returns the absolute value of the Laplace
filtered image (ResultType = 'absolute') in a
byte or uint2 image or the signed result (ResultType =
'signed' or 'signed_clipped'). Here, the output
image type has the same number of bytes per pixel as the input image
(i.e., int1 or int2) for 'signed_clipped', while the output
image has the next larger number of pixels (i.e., int2 or int4) for
'signed'.
Note that filter operators may return unexpected results if an image with a reduced domain is used as input. Please refer to the chapter Filters.
Image (input_object) (multichannel-)image(-array) → object (byte / uint2)
Input image.
ImageLaplace (output_object) (multichannel-)image(-array) → object (byte / uint2 / int2 / int2 / int4)
Laplace-filtered result image.
ResultType (input_control) string → (string)
Type of the result image, whereas for byte and uint2 the absolute value is used.
Default value: 'absolute'
List of values: 'absolute', 'absolute_binomial', 'signed', 'signed_binomial', 'signed_clipped', 'signed_clipped_binomial'
MaskSize (input_control) integer(-array) → (integer)
Size of filter mask.
Default value: 3
List of values: 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39
FilterMask (input_control) string → (string)
Filter mask used in the Laplace operator
Default value: 'n_4'
List of values: 'n_4', 'n_8', 'n_8_isotropic'
read_image(&Image,"mreut"); laplace(Image,&Laplace,"signed",3,"n_8_isotropic"); zero_crossing(Laplace,&ZeroCrossings);
laplace returns 2 (H_MSG_TRUE) if all parameters are correct. If the
input is empty the behavior can be set via
set_system('no_object_result',<Result>). If necessary, an
exception is raised.
zero_crossing,
dual_threshold,
threshold
diff_of_gauss,
laplace_of_gauss,
derivate_gauss
Foundation