imreconstruct

Morphological reconstruction

Syntax

J = imreconstruct(marker,mask)

J = imreconstruct(marker,mask,conn)

Description

J = imreconstruct(marker,mask) performs morphological reconstruction of the image marker under the image mask, and returns the reconstruction in J. The elements of marker must be less than or equal to the corresponding elements of mask. If the values in marker are greater than corresponding elements in mask, then imreconstruct clips the values to the mask level before starting the procedure.

J = imreconstruct(marker,mask,conn) performs morphological reconstruction with the specified connectivity, conn.

Examples

Perform Opening-by-Reconstruction to Identify High Intensity Objects

Read and display a grayscale image.

I = imread('snowflakes.png');
imshow(I)

Adjust the contrast of the image to create the mask image and display results.

mask = adapthisteq(I);
imshow(mask)

Create a marker image that identifies high-intensity objects in the image using morphological erosion and display results.

se = strel('disk',5);
marker = imerode(mask,se);
imshow(marker)

Perform morphological opening on the mask image, using the marker image to identify high-intensity objects in the mask. Display the result.

obr = imreconstruct(marker,mask);
imshow(obr,[])

Use Reconstruction to Segment an Image

Read a logical image into workspace and display it. This is the mask image.

mask = imread('text.png');
figure
imshow(mask)

Create a marker image that identifies the object in the image you want to extract through segmentation. For this example, identify the "w" in the word "watershed".

marker = false(size(mask));
marker(13,94) = true;

Perform segmentation of the mask image using the marker image.

im = imreconstruct(marker,mask);
figure
imshow(im)

Input Arguments

marker — Input image

numeric array | logical array

Input image, specified as a numeric or logical array.

Example: se = strel('disk',5); marker = imerode(mask,se);

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

mask — Mask image

numeric array | logical array

Mask image, specified as a numeric or logical array of the same size and data type as marker.

Example: mask = imread('text.png');

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

conn — Pixel connectivity

4 | 8 | 6 | 18 | 26 | 3-by-3-by- ... -by-3 matrix of 0s and 1s

Pixel connectivity, specified as one of the values in this table. The default connectivity is 8 for 2-D images, and 26 for 3-D images.

Value	Meaning
Two-Dimensional Connectivities
4	Pixels are connected if their edges touch. The neighborhood of a pixel are the adjacent pixels in the horizontal or vertical direction.	Current pixel is shown in gray.
8	Pixels are connected if their edges or corners touch. The neighborhood of a pixel are the adjacent pixels in the horizontal, vertical, or diagonal direction.	Current pixel is shown in gray.
Three-Dimensional Connectivities
6	Pixels are connected if their faces touch. The neighborhood of a pixel are the adjacent pixels in: One of these directions: in, out, left, right, up, and down	Current pixel is shown in gray.
18	Pixels are connected if their faces or edges touch. The neighborhood of a pixel are the adjacent pixels in: One of these directions: in, out, left, right, up, and down A combination of two directions, such as right-down or in-up	Current pixel is center of cube.
26	Pixels are connected if their faces, edges, or corners touch. The neighborhood of a pixel are the adjacent pixels in: One of these directions: in, out, left, right, up, and down A combination of two directions, such as right-down or in-up A combination of three directions, such as in-right-up or in-left-down	Current pixel is center of cube.

For higher dimensions, imreconstruct uses the default value conndef(ndims(marker),'maximal').

Connectivity can also be defined in a more general way for any dimension by specifying a 3-by-3-by- ... -by-3 matrix of 0s and 1s. The 1-valued elements define neighborhood locations relative to the center element of conn. Note that conn must be symmetric about its center element. See Specifying Custom Connectivities for more information.

Data Types: double | logical

Output Arguments

J — Reconstructed image

numeric array | logical array

Reconstructed image, returned as a numeric or logical array, depending on the input image, that is the same size as the input image.

Tips

• Morphological reconstruction is the algorithmic basis for several other Image Processing Toolbox™ functions, including imclearborder, imkeepborder, imextendedmax, imextendedmin, imfill, imhmax, imhmin, and imimposemin.

• Performance note: This function may take advantage of hardware optimization for data types logical, uint8, uint16, single, and double to run faster. Hardware optimization requires marker and mask to be 2-D images and conn to be either 4 or 8.

Algorithms

imreconstruct uses the fast hybrid grayscale reconstruction algorithm described in [1].

References

[1] Vincent, L., "Morphological Grayscale Reconstruction in Image Analysis: Applications and Efficient Algorithms," IEEE Transactions on Image Processing, Vol. 2, No. 2, April, 1993, pp. 176-201.

Extended Capabilities

C/C++ Code Generation

Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

• imreconstruct supports the generation of C code (requires MATLAB^® Coder™). Note that if you choose the generic MATLAB Host Computer target platform, imreconstruct generates code that uses a precompiled, platform-specific shared library. Use of a shared library preserves performance optimizations but limits the target platforms for which code can be generated. For more information, see Types of Code Generation Support in Image Processing Toolbox.

• When generating code, the optional third input argument, conn, must be a compile-time constant, and can only take the value 4 or 8.

• imreconstruct does not support uint64 and int64 data types for code generation.

GPU Code Generation

Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.

Usage notes and limitations:

• When generating code, the optional third input argument, conn, must be a compile-time constant, and can only take the value 4 or 8.

• imreconstruct does not support uint64 and int64 data types for code generation.

Thread-Based Environment

Run code in the background using MATLAB® backgroundPool or accelerate code with Parallel Computing Toolbox™ ThreadPool.

This function fully supports thread-based environments. For more information, see Run MATLAB Functions in Thread-Based Environment.

GPU Arrays

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

Usage notes and limitations:

• Input images must be 2-D numeric or logical matrices. imreconstruct does not support RGB images and 3-D images on a GPU.

• Only the 2-D connectivities (4 and 8) are supported.

For more information, see Image Processing on a GPU.

Version History

Introduced before R2006a

R2022b: Support for thread-based environments

imreconstruct now supports thread-based environments.