

crispening IMAGE 
Applies the crispening algorithm to IMAGE and returns the result.
Supported types: Byte  
sobel IMAGE [ jobMask = sobelNWSEsobelNESW, conversionType = conversionScaleAbs, combineType = combineMaxAbs, divisor = 1] 
Applies Sobel edge detector to IMAGE.
Supported types: Byte Parameters:
conversionType and <combineType> parameters described in combine.  
GEF IMAGE [ a0 = 1.3, s = 0.7] 
Applies GEF algorithm ( first derivative operator for symmetric exponential filter) to IMAGE.
Supported types: Byte  
SDEF IMAGE [ a0 = 1.3, s = 0.7] 
Applies SDEF algorithm ( second derivative operator for symmetric exponential filter) to IMAGE.
Supported types: Byte  
deriche IMAGE [ alpha ] 
Applies Deriche edge detector.
Supported types: Byte  
filter3x3 IMAGE [ matrix, expandEdges = 0, edgecolor = 0, conversionType = conversionScaleAbs, rawOutput = 0, divisor = 1 ] 
Applies convolution with a custom 3x3 kernel, passed in matrix.
Supported types: Byte Parameters:
 
median IMAGE [ w = 3, h = 3 ]  Performs adaptive thresholding with median filter with window dimensions w and h.  
unionFind IMAGE [ method, threshold ] 
Applies a union find algorithm selected by method. The only implemented
method is averagebased region grow ( ’ave’ string constant ). Its only
parameter is threshold, integer value of the balance merger function.
Supported types: Byte  
hysteresis IMAGE, thresold => [ thr0, thr1], neighborhood => 4 or 8 
Perform binary hysteresis thresholding of Byte image with two thresholds,
thr0 and thr1. A pixel is set to 1, if its value is larger than thr1 or
if it is larger than thr0 and the pixel is adjacent to already marked pixels.
Default value of neighborhood is 8. Supported types: Byte  
gaussian SIZE, SIGMA  Generates a square image of the given SIZe and populates with with gaussian function with given SIGMA.  
laplacian SIZE, SIGMA  Generates a square image of the given SIZe and populates with with inverse gaussian function with given SIGMA.  
gradients IMAGE 
This function computes a twodimensional gradient (magnitude and direction) of
an image, using two convolution kernels. The magnitude is computed as the
vector magnitude of the output of the two kernels, and the direction is
computed as the angle between the two orthogonal gradient vectors.
The convolution kernels are (currently limited to) 3x3 masks for calculating separate vertical and horizontal derivatives. (Copyright (c) 1988 by the University of Arizona Digital Image Analysis Lab).  
canny IMAGE [ size = 3, sigma = 2, ridge = 0 ]  First part of the Canny edge detector (without ridge strength selection). The ridge strength must be supplied by the user.  
nms IMAGE [ set = 255, clear = 0 ]  Applies nonmaximal suppression to the image, and replaces all nonmaximal pixels with the clear color, and maximal with set color.  
scale IMAGE [ size = 3, sigma_square = 4 ]  Convolves a given image with a gaussian, where the latter is calculated with the given size and square root of sigma_square.  
ridge IMAGE [ anorm = false, mul = 1, scale = 2, size = 3 ]  First part of the Lindeberg edge detector (without scale selection). The scale must be supplied by the user. size is used in generation of the gaussian kernel. mul is the custom multiply factor to the calclated ridge strength, the maximum absolute value to the principal curvatures. anorm selects whether the Laplacian blob response should be included ( false ) ), or suppressed ( true ).  
convolution IMAGE, KERNEL  Convolves IMAGE with the given KERNEL.  
zerocross IMAGE, cmp = 0  Creates a map from IMAGE where white pixels are assigned to spots where image crosses the zero plane. The zero level is 0 by default, but can be changed by setting the cmp argument.  
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