deviation

deviation_image ( Image : ImageDeviation : Width, Height : )

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.

Parameters

`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.

`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)`

Example

read_image(Image,'fabrik') 
disp_image(Image,WindowHandle)
deviation_image(Image,Deviation,9,9) 
disp_image(Deviation,WindowHandle).

Result

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.

Parallelization Information

deviation_image is reentrant and automatically parallelized (on tuple level, channel level).

Possible Successors

disp_image

Alternatives

entropy_image, entropy_gray

Module

Image filters