Calculate the standard deviation of gray values within rectangular windows.
deviation_image calculates the standard deviation of gray values in the image Image within a rectangular mask of size (Height, Width). The resulting image is returned in ImageDeviation. To better use the range of gray values available in the output image, the result is multiplied by 2. If the parameters Height and Width are even, they are changed to the next larger odd value. At the image borders the gray values are mirrored.
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Image (input_object) |
(multichannel-)image(-array) -> object : byte / int4 / real / int2 / uint2 |
| Image for which the standard deviation is to be calculated. | |
|
ImageDeviation (output_object) |
image(-array) -> object : byte / int4 / real / int2 / uint2 |
| Image containing the standard deviation. | |
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Width (input_control) |
extent.x -> integer |
| Width of the mask in which the standard deviation is calculated. | |
| Default value: 11 | |
| List of values: 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25 | |
| Restriction: (3 <= Width) && odd(Width) | |
|
Height (input_control) |
extent.y -> integer |
| Height of the mask in which the standard deviation is calculated. | |
| Default value: 11 | |
| List of values: 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25 | |
| Restriction: (3 <= Height) && odd(Height) | |
read_image(Image,'fabrik') disp_image(Image,WindowHandle) deviation_image(Image,Deviation,9,9) disp_image(Deviation,WindowHandle).
deviation_image returns 2 (H_MSG_TRUE) if all parameters are correct. If the input is empty the behaviour can be set via set_system('no_object_result',<Result>). If necessary, an exception handling is raised.
deviation_image is reentrant and automatically parallelized (on tuple level, channel level, domain level).
convol_image, texture_laws, intensity
Foundation