AdaptiveHistogramEqualization
Performs a local histogram equalization.
Access to parameter description
This algorithm performs a local histogram equalization of image $I$ onto $O$. The definition is the same as for HistogramEqualization, except that the image is divided in squared windows of a user-defined size, and the equalization is performed in each window. The window size is specified as the number of pixels it contains. The maximum size is 64 (that is, an $8\times8$ square window).
See also
Access to parameter description
This algorithm performs a local histogram equalization of image $I$ onto $O$. The definition is the same as for HistogramEqualization, except that the image is divided in squared windows of a user-defined size, and the equalization is performed in each window. The window size is specified as the number of pixels it contains. The maximum size is 64 (that is, an $8\times8$ square window).
See also
Function Syntax
This function returns outputImage.
// Function prototype
std::shared_ptr< iolink::ImageView > adaptiveHistogramEqualization( std::shared_ptr< iolink::ImageView > inputImage, int32_t neighborhoodSize, std::shared_ptr< iolink::ImageView > outputImage = NULL );
This function returns outputImage.
// Function prototype. adaptive_histogram_equalization( input_image, neighborhood_size = 16, output_image = None )
This function returns outputImage.
// Function prototype. public static IOLink.ImageView AdaptiveHistogramEqualization( IOLink.ImageView inputImage, Int32 neighborhoodSize = 16, IOLink.ImageView outputImage = null );
Class Syntax
Parameters
Parameter Name | Description | Type | Supported Values | Default Value | |
---|---|---|---|---|---|
inputImage |
The input image. | Image | Binary, Label, Grayscale or Multispectral | nullptr | |
neighborhoodSize |
The number of pixels of the square window. A size of 16 amounts to a square of 4-pixels per side. | Int32 | [4, 64] | 16 | |
outputImage |
The output image. Its dimensions are forced to the same values as the input. Its type is automatically changed. | Image | nullptr |
Parameter Name | Description | Type | Supported Values | Default Value | |
---|---|---|---|---|---|
input_image |
The input image. | image | Binary, Label, Grayscale or Multispectral | None | |
neighborhood_size |
The number of pixels of the square window. A size of 16 amounts to a square of 4-pixels per side. | int32 | [4, 64] | 16 | |
output_image |
The output image. Its dimensions are forced to the same values as the input. Its type is automatically changed. | image | None |
Parameter Name | Description | Type | Supported Values | Default Value | |
---|---|---|---|---|---|
inputImage |
The input image. | Image | Binary, Label, Grayscale or Multispectral | null | |
neighborhoodSize |
The number of pixels of the square window. A size of 16 amounts to a square of 4-pixels per side. | Int32 | [4, 64] | 16 | |
outputImage |
The output image. Its dimensions are forced to the same values as the input. Its type is automatically changed. | Image | null |
Object Examples
auto foam = readVipImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "foam.vip" ); AdaptiveHistogramEqualization adaptiveHistogramEqualizationAlgo; adaptiveHistogramEqualizationAlgo.setInputImage( foam ); adaptiveHistogramEqualizationAlgo.setNeighborhoodSize( 16 ); adaptiveHistogramEqualizationAlgo.execute(); std::cout << "outputImage:" << adaptiveHistogramEqualizationAlgo.outputImage()->toString();
foam = imagedev.read_vip_image(imagedev_data.get_image_path("foam.vip")) adaptive_histogram_equalization_algo = imagedev.AdaptiveHistogramEqualization() adaptive_histogram_equalization_algo.input_image = foam adaptive_histogram_equalization_algo.neighborhood_size = 16 adaptive_histogram_equalization_algo.execute() print( "output_image:", str( adaptive_histogram_equalization_algo.output_image ) )
ImageView foam = Data.ReadVipImage( @"Data/images/foam.vip" ); AdaptiveHistogramEqualization adaptiveHistogramEqualizationAlgo = new AdaptiveHistogramEqualization { inputImage = foam, neighborhoodSize = 16 }; adaptiveHistogramEqualizationAlgo.Execute(); Console.WriteLine( "outputImage:" + adaptiveHistogramEqualizationAlgo.outputImage.ToString() );
Function Examples
auto foam = readVipImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "foam.vip" ); auto result = adaptiveHistogramEqualization( foam, 16 ); std::cout << "outputImage:" << result->toString();
foam = imagedev.read_vip_image(imagedev_data.get_image_path("foam.vip")) result = imagedev.adaptive_histogram_equalization( foam, 16 ) print( "output_image:", str( result ) )
ImageView foam = Data.ReadVipImage( @"Data/images/foam.vip" ); IOLink.ImageView result = Processing.AdaptiveHistogramEqualization( foam, 16 ); Console.WriteLine( "outputImage:" + result.ToString() );