add_noise_distribution — Add noise to an image.
add_noise_distribution(Image : ImageNoise : Distribution : )
add_noise_distribution adds noise distributed according to
Distribution to the Image. The resulting gray values are
clipped to the range of the corresponding pixel type.
The Distribution is stored in a tuple of length 513. The individual
values of this tuple define the frequency of noise with a specific amplitude
defined by the position within the tuple. The central value, i.e., the
value at the position 256 in the tuple defines the frequency of pixels that
are not changed. The value at the position 255 defines the frequency of
pixels for which the grayvalue is decreased by 1. The value at the position
254 defines the respective frequency for a grayvalue decrease of 2, and so
on. Analogously, the value at position 257 defines the frequency of pixels
for which the grayvalue is increased by 1.
The Distribution represents salt and pepper noise if at most one
value at a position smaller than 256 is not equal to zero and at most one
value at a position larger than 256 is not equal to zero. In case of salt
and pepper noise, the added noisy pixels are set to the minimum (pepper) and
maximum (salt) values that can be represented by ImageNoise if the
amount of pepper is indicated by the value at position 0 and the amount of
salt is indicated by the value at position 512 in the tuple.
The random noise is generated using the C function “drand48()”.
See the parameter 'seed_rand' of set_system for
information on the used random seed.
Image (input_object) (multichannel-)image(-array) → object (byte / int2)
Input image.
ImageNoise (output_object) (multichannel-)image(-array) → object (byte / int2)
Noisy image.
Number of elements: ImageNoise == Image
Distribution (input_control) distribution.values-array → (real)
Noise distribution.
Number of elements: 513
read_image(Image,'mreut') dev_display (Image) sp_distribution(30,30,Dist) add_noise_distribution(Image,ImageNoise,Dist) dev_display (ImageNoise)
add_noise_distribution 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.
gauss_distribution,
sp_distribution,
noise_distribution_mean
sp_distribution,
gauss_distribution,
noise_distribution_mean,
add_noise_white
Foundation