Linear Filtering

The convolution functions use linear combinations of neighboring pixels to highlight some features in an image.

    

A gradient X filter source and the destination image

● All the convolution functions can be destructive, meaning that the destination image overwrites the source image.
□ These destructive operations are faster.
● Most of these functions have an EImageBW8, an EImageBW16 and an EImageC24 equivalent.
● Open eVision offers 2 ways of doing convolutions:
□ Use a predefined method with a predefined filter, and in some cases, a kernel size.
□ Create your own EKernel and use the function ConvolKernel.

Predefined filters

The available predefined filters are:

● ConvolLowpass1
● ConvolLowpass2
● ConvolLowpass3
● ConvolHighpass1
● ConvolHighpass2
● ConvolGradient
● ConvolGradientX
● ConvolGradientY
● ConvolLaplacian4
● ConvolLaplacian8
● ConvolLaplacianX
● ConvolLaplacianY
● ConvolPrewitt
● ConvolPrewittX
● ConvolPrewittY
● ConvolSobel
● ConvolSobelX
● ConvolSobelY
● ConvolRoberts
● ConvolUniform
● ConvolGaussian
● ConvolGabor

Customized EKernel

When you use your own kernel:

● You can choose the width and height of the kernel.
□ Use SetKernelData to fill the convolution coefficients.
● Open eVision automatically normalizes the kernel coefficients so that their sum is 1.
□ If you define a Gain (multiplying all resulting pixels by that value) and an Offset (adding that value to all resulting pixels), they are applied after that normalization.
□ Note that using any gain other than 1 can lead to a saturation in the resulting image and an overflow or an underflow during the internal calculations.
● To rectify any value (to keep only the positive ones for instance), set an EKernelRectifier.
● The outside value is used for the border calculations (when the kernel needs values from out of the image on the border of the image to compute the result).
● Another way to create a kernel is by giving the constructor an EKernelType. This is quite similar to the way of doing a convolution with a predefined filter.
2 The following tutorial illustrates an application using a custom EKernel in Open eVision Studio: Enhancing an X-ray image.