| Operators |
median_separate — Separated median filtering with rectangle masks.
median_separate(Image : ImageSMedian : MaskWidth, MaskHeight, Margin : )
The operator median_separate carries out a variation of the median filtering: First two auxiliary images are created. The first one originates from a median filtering with a horizontal mask having a height of one pixel and the width MaskWidth followed by filtering with a vertical mask having the height MaskHeight and width of one pixel. The second auxiliary image is created by filtering with the same masks, but with a reversed sequence of the operation: first the vertical, then the horizontal mask. The output image results from averaging the two auxiliary images pixel by pixel.
The operator median_separate is clearly faster than the normal operator median_image because both masks are one pixel wide, facilitating a very effecient processing. The runtime is practically independent of the size of the mask. For example, the operator median_separate can be well used after texture filters, where large masks are needed.
The filter can also be used several times in a row in order to enhance the smoothing.
For an explanation of the concept of smoothing filters see the introduction of chapter Filters / Smoothing.
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 to be filtered.
Median filtered image.
Width of rank mask.
Default value: 25
Suggested values: 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 27, 43, 51, 67, 91, 121, 151
Typical range of values: 1 ≤ MaskWidth ≤ 401
Minimum increment: 2
Recommended increment: 2
Height of rank mask.
Default value: 25
Suggested values: 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 27, 43, 51, 67, 91, 121, 151
Typical range of values: 1 ≤ MaskHeight ≤ 401
Minimum increment: 2
Recommended increment: 2
Border treatment.
Default value: 'mirrored'
Suggested values: 'mirrored', 'cyclic', 'continued', 0, 30, 60, 90, 120, 150, 180, 210, 240, 255
read_image(Image,'fabrik') median_separate(Image,MedianSeparate,5,5,3) dev_display(MedianSeparate)
For each pixel: O(40).
texture_laws, sobel_amp, deviation_image
learn_ndim_norm, regiongrowing, auto_threshold
R. Haralick, L. Shapiro; “Computer and Robot Vision”; Addison-Wesley, 1992, Seite 319
Foundation
| Operators |