ImageDev

DobFilter2d

Appproximates a Laplacian as the difference of two box filters applied on the same two-dimensional image.

Access to parameter description

For an introduction: DobFilter2d calculates the difference between two local averages computed over square neighborhoods of different kernel sizes (Difference Of Boxes) applied on the same image. The operation consists of the same filter performed with two different kernel sizes.
The size of the kernels must be an odd number.

This operation applied to a 1D step edge is shown in Figure 1.
<b> Figure 1.</b> DOB approximation
Figure 1. DOB approximation

DobFilter2d does not compute the Laplacian of an image, but is a good approximation and has the main advantage of not generating isolated points.

Typical ratios of the neighborhood sizes (width of Box1 / width of Box2) has a range between 1.5 and 2.5. Box1 and Box2 are respectively parametrized by the parameters largeBoxSize and smallBoxSize.
For example, kernels of size 5x5/3x3 or 9x9/5x5 can be used.

To keep a correct representation of the edges and a maximum of detail, using too large a kernel is not recommended (3, 5 and 7 are the most frequent values).

The deviation between the two masks has a direct effect on the edges. If the difference is too large, the edges are very thick and all small details disappear. If the difference is small (less than 4), the edges are very thin and details more precise.

See also

Function Syntax

This function returns outputImage. 
// Function prototype
std::shared_ptr< iolink::ImageView >
dobFilter2d( std::shared_ptr< iolink::ImageView > inputImage,
             int32_t smallBoxSize,
             int32_t largeBoxSize,
             std::shared_ptr< iolink::ImageView > outputImage = nullptr );
This function returns outputImage. 
// Function prototype.
dob_filter_2d(input_image: idt.ImageType,
              small_box_size: int = 3,
              large_box_size: int = 7,
              output_image: idt.ImageType = None) -> idt.ImageType
This function returns outputImage. 
// Function prototype.
public static IOLink.ImageView
DobFilter2d( IOLink.ImageView inputImage,
             Int32 smallBoxSize = 3,
             Int32 largeBoxSize = 7,
             IOLink.ImageView outputImage = 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
smallBoxSize
The size of the small box. Int32 >=1 3
input
largeBoxSize
The size of the large box. Int32 >=1 7
output
outputImage
The output image. Image nullptr
Parameter Name Description Type Supported Values Default Value
input
input_image
The input image. image Binary, Label, Grayscale or Multispectral None
input
small_box_size
The size of the small box. int32 >=1 3
input
large_box_size
The size of the large box. int32 >=1 7
output
output_image
The output image. image None
Parameter Name Description Type Supported Values Default Value
input
inputImage
The input image. Image Binary, Label, Grayscale or Multispectral null
input
smallBoxSize
The size of the small box. Int32 >=1 3
input
largeBoxSize
The size of the large box. Int32 >=1 7
output
outputImage
The output image. Image null

Object Examples

auto polystyrene = ioformat::readImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "polystyrene.tif" );

DobFilter2d dobFilter2dAlgo;
dobFilter2dAlgo.setInputImage( polystyrene );
dobFilter2dAlgo.setSmallBoxSize( 3 );
dobFilter2dAlgo.setLargeBoxSize( 7 );
dobFilter2dAlgo.execute();

std::cout << "outputImage:" << dobFilter2dAlgo.outputImage()->toString();

polystyrene = ioformat.read_image(imagedev_data.get_image_path("polystyrene.tif"))

dob_filter_2d_algo = imagedev.DobFilter2d()
dob_filter_2d_algo.input_image = polystyrene
dob_filter_2d_algo.small_box_size = 3
dob_filter_2d_algo.large_box_size = 7
dob_filter_2d_algo.execute()

print("output_image:", str(dob_filter_2d_algo.output_image))

ImageView polystyrene = ViewIO.ReadImage( @"Data/images/polystyrene.tif" );

DobFilter2d dobFilter2dAlgo = new DobFilter2d
{
    inputImage = polystyrene,
    smallBoxSize = 3,
    largeBoxSize = 7
};
dobFilter2dAlgo.Execute();

Console.WriteLine( "outputImage:" + dobFilter2dAlgo.outputImage.ToString() );

Function Examples

auto polystyrene = ioformat::readImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "polystyrene.tif" );

auto result = dobFilter2d( polystyrene, 3, 7 );

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

polystyrene = ioformat.read_image(imagedev_data.get_image_path("polystyrene.tif"))

result = imagedev.dob_filter_2d(polystyrene, 3, 7)

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

ImageView polystyrene = ViewIO.ReadImage( @"Data/images/polystyrene.tif" );

IOLink.ImageView result = Processing.DobFilter2d( polystyrene, 3, 7 );

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