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 = nullptr );
This function returns outputImage.
// Function prototype.
adaptive_histogram_equalization(input_image: idt.ImageType,
neighborhood_size: int = 16,
output_image: idt.ImageType = None) -> idt.ImageType
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 | |
|---|---|---|---|---|---|
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inputImage |
The input image. | Image | Binary, Label, Grayscale or Multispectral | nullptr |
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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 |
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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 | |
|---|---|---|---|---|---|
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input_image |
The input image. | image | Binary, Label, Grayscale or Multispectral | None |
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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 |
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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 |
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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() );
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