ImageDev

RegionalMaxima

Computes the regional maxima in a grayscale image and marks them in a binary image.

Access to parameter description

This command is deprecated, it will be removed in ImageDev 2024.2.
You can use RegionalExtrema2d or RegionalExtrema3d instead.

For an introduction: This algorithm computes the regional or relative maxima in a grayscale image $I$ and creates a binary image $O$ containing these maxima.

A regional maximum $C$ is a set of connected pixels such that:

<b> Figure 1.</b> One-dimensional example of a regional maxima detection
Figure 1. One-dimensional example of a regional maxima detection

This algorithm is based on [1] and uses a recursive method combined with a geodesic propagation.
To avoid getting too many regions in the output image, input should be smoothed first with a low-pass filter or with the numerical reconstruction algorithm.




Figure 2. Original image (left) and regional maxima in red (right)


Reference:
[1] B. Laÿ. "Recursive Algorithms in Mathematical Morphology", In Acta Stereologica, vol.6/III, pp.691-696, 7th International Congress For Stereology, Caen, France, Sept. 1987.

See also

Function Syntax

This function returns outputBinaryImage. 
// Function prototype
std::shared_ptr< iolink::ImageView >
regionalMaxima( std::shared_ptr< iolink::ImageView > inputImage,
                RegionalMaxima::Neighborhood neighborhood,
                std::shared_ptr< iolink::ImageView > outputBinaryImage = NULL );
This function returns outputBinaryImage. 
// Function prototype.
regional_maxima( input_image, neighborhood = RegionalMaxima.Neighborhood.CONNECTIVITY_26, output_binary_image = None )
This function returns outputBinaryImage. 
// Function prototype.
public static IOLink.ImageView
RegionalMaxima( IOLink.ImageView inputImage,
                RegionalMaxima.Neighborhood neighborhood = ImageDev.RegionalMaxima.Neighborhood.CONNECTIVITY_26,
                IOLink.ImageView outputBinaryImage = null );

Class Syntax

Parameters

Parameter Name Description Type Supported Values Default Value
input
inputImage
The input image. Image Binary, Label, Grayscale or Multispectral nullptr
input
neighborhood
The 3D neighborhood configuration. This parameter is ignored with a 2D input image.
CONNECTIVITY_6 The structuring element is composed of voxels with a common face with the voxel of interest.
CONNECTIVITY_18 The structuring element is composed of voxels with at least one common edge.
CONNECTIVITY_26 The structuring element is a full cube.
Enumeration CONNECTIVITY_26
output
outputBinaryImage
The binary output image. Its dimensions and type are forced to the same values as the input. Image nullptr
Parameter Name Description Type Supported Values Default Value
input
input_image
The input image. image Binary, Label, Grayscale or Multispectral None
input
neighborhood
The 3D neighborhood configuration. This parameter is ignored with a 2D input image.
CONNECTIVITY_6 The structuring element is composed of voxels with a common face with the voxel of interest.
CONNECTIVITY_18 The structuring element is composed of voxels with at least one common edge.
CONNECTIVITY_26 The structuring element is a full cube.
enumeration CONNECTIVITY_26
output
output_binary_image
The binary output image. Its dimensions and type are forced to the same values as the input. image None
Parameter Name Description Type Supported Values Default Value
input
inputImage
The input image. Image Binary, Label, Grayscale or Multispectral null
input
neighborhood
The 3D neighborhood configuration. This parameter is ignored with a 2D input image.
CONNECTIVITY_6 The structuring element is composed of voxels with a common face with the voxel of interest.
CONNECTIVITY_18 The structuring element is composed of voxels with at least one common edge.
CONNECTIVITY_26 The structuring element is a full cube.
Enumeration CONNECTIVITY_26
output
outputBinaryImage
The binary output image. Its dimensions and type are forced to the same values as the input. Image null

Object Examples

auto foam = readVipImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "foam.vip" );

RegionalMaxima regionalMaximaAlgo;
regionalMaximaAlgo.setInputImage( foam );
regionalMaximaAlgo.setNeighborhood( RegionalMaxima::Neighborhood::CONNECTIVITY_26 );
regionalMaximaAlgo.execute();

std::cout << "outputBinaryImage:" << regionalMaximaAlgo.outputBinaryImage()->toString();

foam = imagedev.read_vip_image(imagedev_data.get_image_path("foam.vip"))

regional_maxima_algo = imagedev.RegionalMaxima()
regional_maxima_algo.input_image = foam
regional_maxima_algo.neighborhood = imagedev.RegionalMaxima.CONNECTIVITY_26
regional_maxima_algo.execute()

print( "output_binary_image:", str( regional_maxima_algo.output_binary_image ) )

ImageView foam = Data.ReadVipImage( @"Data/images/foam.vip" );

RegionalMaxima regionalMaximaAlgo = new RegionalMaxima
{
    inputImage = foam,
    neighborhood = RegionalMaxima.Neighborhood.CONNECTIVITY_26
};
regionalMaximaAlgo.Execute();

Console.WriteLine( "outputBinaryImage:" + regionalMaximaAlgo.outputBinaryImage.ToString() );

Function Examples

auto foam = readVipImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "foam.vip" );

auto result = regionalMaxima( foam, RegionalMaxima::Neighborhood::CONNECTIVITY_26 );

std::cout << "outputBinaryImage:" << result->toString();

foam = imagedev.read_vip_image(imagedev_data.get_image_path("foam.vip"))

result = imagedev.regional_maxima( foam, imagedev.RegionalMaxima.CONNECTIVITY_26 )

print( "output_binary_image:", str( result ) )

ImageView foam = Data.ReadVipImage( @"Data/images/foam.vip" );

IOLink.ImageView result = Processing.RegionalMaxima( foam, RegionalMaxima.Neighborhood.CONNECTIVITY_26 );

Console.WriteLine( "outputBinaryImage:" + result.ToString() );