Determine the noise distribution of an image.
::noise_distribution_mean calculates the noise distribution in a region of the image Image. The parameter ConstRegion determines a region of the image with approximately constant gray values. Ideally, the changes in gray values should only be caused by noise in this region. From this region the noise distribution is determined by using the ::mean_image operator to smooth the image, and to use the gray value differences in this area as an estimate for the noise distribution, which is returned in Distribution.
It is important to ensure that the region ConstRegion is not too close to a large gradient in the image, because the gradient values are then used for calculating the mean. This means the the distance of ConstRegion must be at least as large as the filter size FilterSize used for calculating the mean.
|
ConstRegion (input_object) |
region(-array) -> Hobject: HRegion(Array) |
| Region from which the noise distribution is to be estimated. | |
|
Image (input_object) |
image -> Hobject: HImage ( byte ) |
| Corresponding image. | |
|
FilterSize (input_control) |
integer -> HTuple.long |
| Size of the mean filter. | |
| Default value: 21 | |
| Suggested values: 5, 11, 15, 21, 31, 51, 101 | |
| Typical range of values: 3 <= FilterSize <= 501 (lin) | |
| Minimum increment: 2 | |
|
Recommended increment: 2 | |
|
Distribution (output_control) |
distribution.values-array -> HTuple.double * |
| Noise distribution of all input regions. | |
::draw_region, ::gen_circle, ::gen_ellipse, ::gen_rectangle1, ::gen_rectangle2, ::threshold, ::erosion_circle, ::gauss_image, ::smooth_image, ::sub_image
::add_noise_distribution, ::disp_distribution
::mean_image, ::gauss_distribution
Image filters
