| Image Processing Toolbox User's Guide | ![]() |
Syntax
Description
I2 = imimposemin(I,BW)
modifies the intensity image I using morphological reconstruction so it only has regional minima wherever BW is nonzero. BW is a binary image the same size as I.
By default, imimposemin uses 8-connected neighborhoods for 2-D images and 26-connected neighborhoods for 3-D images. For higher dimensions, imimposemin uses conndef(ndims(I),'minimum').
specifies the connectivity, where I2 = imimposemin(I,BW,CONN)
CONN can have any of the following scalar values.
Connectivity can also be defined in a more general way for any dimension by using for CONN a 3-by-3-by-...-by-3 matrix of 0's and 1's. The 1-valued elements define neighborhood locations relative to the center element of CONN. Note that CONN must be symmetric about its center element.
Class Support
I can be of any nonsparse numeric class and any dimension. BW must be a nonsparse numeric array with the same size as I. I2 has the same size and class as I.
Example
Modify an image so that it only has regional minima at one location.
To show where these pixels of interest fall on the original image, this code superimposes the marker over the mask. The small white square marks the spot. This code is not essential to the impose minima operation.
imimposemin function uses morphological reconstruction of the mask image with the marker image to impose the minima at the specified location. Note how all the dark areas of the original image, except the marked area, are lighter.
imregionalmin return binary images that specify the locations of all the regional minima in both images.
Algorithm
imimposemin uses a technique based on morphological reconstruction.
See Also
conndef, imreconstruct, imregionalmin
| imhmin | imlincomb | ![]() |
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