You are here: Start » Function Reference » Image Local Transforms

Image Local Transforms

Select a function from the list below.

Icon	Name	Description
	CloseImage	E.g. removal of the "pepper" component of salt-and-pepper noise.
	ConvolveImage	Non-standard local transforms defined by the user.
	DifferenceOfGaussians	Emphasizes high-frequency image features such as lines or patches / dots.
	DilateAndErodeImage	Calculates dilation and erosion simultaneously for faster execution.
	DilateImage	Replaces each pixel with the maximum of pixels within a kernel.
	DilateImage_AnyKernel	Replaces each pixel with the maximum of pixels within an arbitrary kernel.
	DilateImage_Mask	Replaces each pixel with the maximum of pixels within a small rectangular kernel.
	ErodeImage	Replaces each pixel with the minimum of pixels within a kernel.
	ErodeImage_AnyKernel	Replaces each pixel with the minimum of pixels within an arbitrary kernel.
	ErodeImage_Mask	Replaces each pixel with the minimum of pixels within a small rectangular kernel.
	GradientDirAndPresenceImage	For highly optimized analysis of gradient directions.
	GradientImage	Computes a gradient image with smoothing operator of any size. The output pixels are signed.
	GradientImage_Mask	Computes a gradient image with a Sobel or Prewitt operator.
	GradientMagnitudeImage	Measures the strength of gradient at each pixel location with Sobel or Prewitt operator.
	MeasureImageGradients	Computes gradient magnitudes of an image.
	NormalizeImageGradients	Adjusts gradient angles to a given range.
	OpenImage	E.g. removal of the "salt" component of salt-and-pepper noise.
	RotateImageGradients	Rotates image gradients.
	SmoothImage_Deriche	Approximation of the gaussian filter, which can be faster for large kernels.
	SmoothImage_Gauss	Removal of gaussian noise from images.
	SmoothImage_Gauss_Mask	Removal of gaussian noise from images (fast).
	SmoothImage_Mean	Usually used for computing features related to local image "windows". Can be also used for noise removal, but Gauss is superior here.
	SmoothImage_Mean_AnyKernel	Usually used for computing features related to local image "windows" having non-standard shape.
	SmoothImage_Mean_Mask	This is a faster alternative to SmoothImage_Mean when the kernel is very small.
	SmoothImage_Median	Edge-preserving noise removal (but slow).
	SmoothImage_Median_Mask	Replaces each pixel with the median of pixels within a 3x3 rectangular kernel (faster).
	SmoothImage_Middle	Useful for calculating per-pixel threshold values for image binarization.