Image Local Transforms

Performs a morphological black top hat (bottom hat) operation on a image using an arbitrary kernel.

Removes small dark structures from an image (or fills in bright ones) by applying consecutive dilation and erosion.

E.g. removal of the "pepper" component of salt-and-pepper noise.

Removes small dark structures from an image (or fills in bright ones) by applying consecutive dilation and erosion.

E.g. removal of the "pepper" component of salt-and-pepper noise.

Applies difference of Gaussians on an image, i.e. computes difference of two Gaussian smoothed images.

Emphasizes high-frequency image features such as lines or patches / dots.

Replaces each pixel with the maximum of pixels within a kernel.

Thickens bright features in an images and thins dark ones.

Replaces each pixel with the maximum of pixels within a small rectangular kernel.

Replaces each pixel with the minimum of pixels within an arbitrary kernel.

Computes an image of gradient directions mapped to the range from 1 to 255. Zero means "no edge".

For highly optimized analysis of gradient directions.

Computes a gradient image with a Sobel or Prewitt operator.

Computes an image of gradient for only selected direction.

For highly optimized analysis of gradient directions.

Removes small bright structures from an image (or fills in dark ones) by applying consecutive erosion and dilation.

E.g. removal of the "salt" component of salt-and-pepper noise.

Smooths an image while preserving sharp edges.

Smooths the result of GradientDirAndPresenceImage.

Smooths an image using a predefined gaussian kernel.

Removal of gaussian noise from images (fast).

Smooths an image by averaging pixels within an arbitrary kernel.

Usually used for computing features related to local image "windows" having non-standard shape.

Replaces each pixel with the median of pixels within a kernel.

Edge-preserving noise removal (but slow).

Replaces each pixel with the average of maximum and minimum calculated within a kernel.

Useful for calculating per-pixel threshold values for image binarization.

Smooths an region by averaging pixels within a rectangular kernel.

Usually used for computing features related to local image "windows". Can be also used for noise removal, but Gauss is superior here.

Performs a morphological white top hat operation on a image using a predefined kernel.

Performs a morphological white top hat operation on a image using a predefined mask.