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# imhmin

H-minima transform

## Syntax

``I2 = imhmin(I,h)``
``I2 = imhmin(I,h,conn)``

## Description

example

````I2 = imhmin(I,h)` suppresses all minima in the intensity image `I` whose depth is less than `h`, where `h` is a scalar. Regional minima are connected components of pixels with a constant intensity value, t, whose external boundary pixels all have a value greater than t. By default, `imhmin` uses 8-connected neighborhoods for 2-D images, and 26-connected neighborhoods for 3-D images. For higher dimensions, `imhmax` uses `conndef(ndims(I),'maximal')`.```
````I2 = imhmin(I,h,conn)` computes the H-minima transform, where `conn` specifies the connectivity.```

## Examples

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Create a sample image with two regional minima.

```a = 10*ones(10,10); a(2:4,2:4) = 7; a(6:8,6:8) = 2```
```a = 10 10 10 10 10 10 10 10 10 10 10 7 7 7 10 10 10 10 10 10 10 7 7 7 10 10 10 10 10 10 10 7 7 7 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 2 2 2 10 10 10 10 10 10 10 2 2 2 10 10 10 10 10 10 10 2 2 2 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 ```

Suppress all minima below a specified value. Note how the region with pixels valued 7 disappears in the transformed image because its depth is less than the specified h value.

`b = imhmin(a,4)`
```b = 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 6 6 6 10 10 10 10 10 10 10 6 6 6 10 10 10 10 10 10 10 6 6 6 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 ```

## Input Arguments

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Input array, specified as a nonsparse numeric array of any dimension.

Example: `I = imread('glass.png'); BW = imhmin(I,80);`

Data Types: `single` | `double` | `int8` | `int16` | `int32` | `int64` | `uint8` | `uint16` | `uint32` | `uint64` | `logical`

h-minima transform, specified as a nonnegative scalar.

Example: `b = imhmin(a,4) `

Data Types: `single` | `double` | `int8` | `int16` | `int32` | `int64` | `uint8` | `uint16` | `uint32` | `uint64`

Connectivity, specified as a one of the scalar values in the following table. By default, `imhmin` uses 8-connected neighborhoods for 2-D images and 26-connected neighborhoods for 3-D images. For higher dimensions, `imhmin` uses `conndef(numel(size(I)),'maximal')`. Connectivity can 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 around its center element.

Value

Meaning

Two-dimensional connectivities

4

4-connected neighborhood

8

8-connected neighborhood

Three-dimensional connectivities

6

6-connected neighborhood

18

18-connected neighborhood

26

26-connected neighborhood

Example: `b = imhmin(a,4,4) `

Data Types: `single` | `double` | `int8` | `int16` | `int32` | `int64` | `uint8` | `uint16` | `uint32` | `uint64`

## Output Arguments

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Transformed image, returned as a nonsparse numeric array of any class, the same size as `I`.

## References

[1] Soille, P., Morphological Image Analysis: Principles and Applications, Springer-Verlag, 1999, pp. 170-171.