LocalAutocorrelationFilter2d
Computes the cross correlation of a two-dimensional image by itself in a given window size.
Access to parameter description
The autocorrelation is given by the formula: $$ O(n,m)=\frac{1}{2K}\sum_{i=-q}^{q}\sum_{j=-r}^{r}g(n-i,m-j) $$ $$ \mbox{where}~ g(l,k)=I(l,k)\times I(l+S,k)+I(l,k)\times I(l,k+S) $$ For a window of size $2q+1$ in X and $2r+1$ in Y.
$K$ is the Normalization coefficient: $K=(2q+1)\times(2r+1)$.
$S$ is autocorrelation offset. In this implementation it is equal to the size of the window: $S=2q+1=2r+1$.
The autocorrelation formula applied here can be written as follows: $$ O(n,m)=\frac{1}{2S^2}\sum_{i=-\frac{S-1}{2}}^{\frac{S-1}{2}}\sum_{j=-\frac{S-1}{2}}^{\frac{S-1}{2}} \left [I(n-i,m-j)\times I(n-i+S,m-j)+I(n-i,m-j)\times I(n-i,m-j+S)\right ] $$
See also
Access to parameter description
The autocorrelation is given by the formula: $$ O(n,m)=\frac{1}{2K}\sum_{i=-q}^{q}\sum_{j=-r}^{r}g(n-i,m-j) $$ $$ \mbox{where}~ g(l,k)=I(l,k)\times I(l+S,k)+I(l,k)\times I(l,k+S) $$ For a window of size $2q+1$ in X and $2r+1$ in Y.
$K$ is the Normalization coefficient: $K=(2q+1)\times(2r+1)$.
$S$ is autocorrelation offset. In this implementation it is equal to the size of the window: $S=2q+1=2r+1$.
The autocorrelation formula applied here can be written as follows: $$ O(n,m)=\frac{1}{2S^2}\sum_{i=-\frac{S-1}{2}}^{\frac{S-1}{2}}\sum_{j=-\frac{S-1}{2}}^{\frac{S-1}{2}} \left [I(n-i,m-j)\times I(n-i+S,m-j)+I(n-i,m-j)\times I(n-i,m-j+S)\right ] $$
See also
Function Syntax
This function returns outputImage.
// Function prototype
std::shared_ptr< iolink::ImageView > localAutocorrelationFilter2d( std::shared_ptr< iolink::ImageView > inputImage, int32_t kernelSize, std::shared_ptr< iolink::ImageView > outputImage = nullptr );
This function returns outputImage.
// Function prototype.
local_autocorrelation_filter_2d(input_image: idt.ImageType,
kernel_size: int = 3,
output_image: idt.ImageType = None) -> idt.ImageType
This function returns outputImage.
// Function prototype.
public static IOLink.ImageView
LocalAutocorrelationFilter2d( IOLink.ImageView inputImage,
Int32 kernelSize = 3,
IOLink.ImageView outputImage = null );
Class Syntax
Parameters
| Parameter Name | Description | Type | Supported Values | Default Value | |
|---|---|---|---|---|---|
 |
inputImage |
The input image. | Image | Grayscale | nullptr |
|
kernelSize |
The size of the kernel (the side length of the square window in pixels). | Int32 | >=1 | 3 |
 |
outputImage |
The output image. Its dimensions are forced to the same values as the input. Its data type is promoted. | Image | nullptr | |
| Parameter Name | Description | Type | Supported Values | Default Value | |
|---|---|---|---|---|---|
|
input_image |
The input image. | image | Grayscale | None |
|
kernel_size |
The size of the kernel (the side length of the square window in pixels). | int32 | >=1 | 3 |
|
output_image |
The output image. Its dimensions are forced to the same values as the input. Its data type is promoted. | image | None | |
| Parameter Name | Description | Type | Supported Values | Default Value | |
|---|---|---|---|---|---|
|
inputImage |
The input image. | Image | Grayscale | null |
|
kernelSize |
The size of the kernel (the side length of the square window in pixels). | Int32 | >=1 | 3 |
|
outputImage |
The output image. Its dimensions are forced to the same values as the input. Its data type is promoted. | Image | null | |
Object Examples
auto polystyrene = ioformat::readImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "polystyrene.tif" ); LocalAutocorrelationFilter2d localAutocorrelationFilter2dAlgo; localAutocorrelationFilter2dAlgo.setInputImage( polystyrene ); localAutocorrelationFilter2dAlgo.setKernelSize( 3 ); localAutocorrelationFilter2dAlgo.execute(); std::cout << "outputImage:" << localAutocorrelationFilter2dAlgo.outputImage()->toString();
polystyrene = ioformat.read_image(imagedev_data.get_image_path("polystyrene.tif"))
local_autocorrelation_filter_2d_algo = imagedev.LocalAutocorrelationFilter2d()
local_autocorrelation_filter_2d_algo.input_image = polystyrene
local_autocorrelation_filter_2d_algo.kernel_size = 3
local_autocorrelation_filter_2d_algo.execute()
print("output_image:", str(local_autocorrelation_filter_2d_algo.output_image))
ImageView polystyrene = ViewIO.ReadImage( @"Data/images/polystyrene.tif" );
LocalAutocorrelationFilter2d localAutocorrelationFilter2dAlgo = new LocalAutocorrelationFilter2d
{
inputImage = polystyrene,
kernelSize = 3
};
localAutocorrelationFilter2dAlgo.Execute();
Console.WriteLine( "outputImage:" + localAutocorrelationFilter2dAlgo.outputImage.ToString() );
Function Examples
auto polystyrene = ioformat::readImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "polystyrene.tif" ); auto result = localAutocorrelationFilter2d( polystyrene, 3 ); std::cout << "outputImage:" << result->toString();
polystyrene = ioformat.read_image(imagedev_data.get_image_path("polystyrene.tif"))
result = imagedev.local_autocorrelation_filter_2d(polystyrene, 3)
print("output_image:", str(result))
ImageView polystyrene = ViewIO.ReadImage( @"Data/images/polystyrene.tif" ); IOLink.ImageView result = Processing.LocalAutocorrelationFilter2d( polystyrene, 3 ); Console.WriteLine( "outputImage:" + result.ToString() );