CvXImgProc Methods

Simple one-line Adaptive Manifold Filter call.

Performs anisotropic diffusian on an image. The function applies Perona-Malik anisotropic diffusion to an image.

Applies the bilateral texture filter to an image. It performs structure-preserving texture filter. For more details about this filter see @cite Cho2014.

Compares a color template against overlapped color image regions.

Computes the estimated covariance matrix of an image using the sliding window forumlation.

Factory method, create instance of AdaptiveManifoldFilter and produce some initialization routines.

Factory method, create instance of DTFilter and produce initialization routines.

Creates a EdgeBoxes

Factory method, create instance of FastGlobalSmootherFilter and execute the initialization routines.

Creates a smart pointer to a FastLineDetector object and initializes it

Factory method, create instance of GuidedFilter and produce initialization routines.

creates a quaternion image.

Creates a RFFeatureGetter

Creates a StructuredEdgeDetection

Class implementing the LSC (Linear Spectral Clustering) superpixels. The function initializes a SuperpixelLSC object for the input image. It sets the parameters of superpixel algorithm, which are: region_size and ruler.It preallocate some buffers for future computing iterations over the given image.An example of LSC is illustrated in the following picture. For enhanced results it is recommended for color images to preprocess image with little gaussian blur with a small 3 x 3 kernel and additional conversion into CieLAB color space.

Initializes a SuperpixelSEEDS object. The function initializes a SuperpixelSEEDS object for the input image. It stores the parameters of the image: image_width, image_height and image_channels.It also sets the parameters of the SEEDS superpixel algorithm, which are: num_superpixels, num_levels, use_prior, histogram_bins and double_step. The number of levels in num_levels defines the amount of block levels that the algorithm use in the optimization.The initialization is a grid, in which the superpixels are equally distributed through the width and the height of the image.The larger blocks correspond to the superpixel size, and the levels with smaller blocks are formed by dividing the larger blocks into 2 x 2 blocks of pixels, recursively until the smaller block level. An example of initialization of 4 block levels is illustrated in the following figure.

Simple one-line Domain Transform filter call. If you have multiple images to filter with the same guided image then use DTFilter interface to avoid extra computations on initialization stage.

Smoothes an image using the Edge-Preserving filter.

Simple one-line Fast Bilateral Solver filter call. If you have multiple images to filter with the same guide then use FastBilateralSolverFilter interface to avoid extra computations.

Simple one-line Fast Global Smoother filter call. If you have multiple images to filter with the same guide then use FastGlobalSmootherFilter interface to avoid extra computations.

Calculates 2D Fast Hough transform of an image.

Applies X Deriche filter to an image.

Applies Y Deriche filter to an image.

Applies Paillou filter to an image.

Applies Paillou filter to an image.

Simple one-line Guided Filter call. If you have multiple images to filter with the same guided image then use GuidedFilter interface to avoid extra computations on initialization stage.

Calculates coordinates of line segment corresponded by point in Hough space.

Applies the joint bilateral filter to an image.

Global image smoothing via L0 gradient minimization.

Applies Niblack thresholding to input image.

Calculates an affine transformation that normalize given image using Pei&Lin Normalization.

Calculates an affine transformation that normalize given image using Pei&Lin Normalization.

calculates conjugate of a quaternion image.

Performs a forward or inverse Discrete quaternion Fourier transform of a 2D quaternion array.

Calculates the per-element quaternion product of two arrays

divides each element by its modulus.

Applies the rolling guidance filter to an image.

Applies a binary blob thinning operation, to achieve a skeletization of the input image. The function transforms a binary blob image into a skeletized form using the technique of Zhang-Suen.

Applies weighted median filter to an image.