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FILTERS(9.1)							  FILTERS(9.1)

       adapt,  ahe,  crispen,  laplace,	 edge, edge2, edge3, extremum, median,
       nonoise,	smooth,	shadepic - image neighborhood operators

       fb/adapt	[ input	]

       fb/ahe [	input ]

       fb/crispen [ input ]

       fb/laplace [ input ]

       fb/edge [ input ]

       fb/edge2	[ input	]

       fb/edge3	[ input	]

       fb/extremum [ input ]

       fb/median [ input ]

       fb/nonoise [ input ]

       fb/smooth [ input ]

       fb/shadepic [ -lx y z ] [ input ]

       Gathered	here are descriptions of programs that compute the  pixels  of
       an  output image	by performing some operation on	a neighborhood of each
       pixel of	their input image  (default  standard  input).	 Each  program
       writes  the  output  image  on  standard	 output.  The programs process
       multi-channel inputs by treating	each channel independently.

       Adapt performs adaptive	contrast  enhancement  by  examining  the  7x7
       region  centered	 on  each input	pixel, remapping the center pixel lin-
       early in	a way that would send the neighborhood's maximum value to  255
       and  its	 minimum  to 0.	 To avoid divide checks, no mapping is done if
       all pixels in the region	have the same value.

       Ahe performs adaptive histogram equalization  by	 examining  the	 17x17
       region  centered	 on  each  input  pixel, counting the number of	pixels
       whose value is less than	the center pixel. (It  counts  A1/2  for  each
       pixel  equal  to	 the center value.)  Output pixel values are 255 times
       the count divided by the	window size.

       Crispen examines	the 3x3	region surrounding each	input pixel, computing
       9 times the center pixel	minus the sum of its eight neighbors.  This is
       a fairly	extreme	high-pass filter and sharpens edges substantially.

       Laplace computes	5 times	the center pixel minus the  sum	 of  its  four
       vertical	 and horizontal	neighbors.  This adds a	3x3 discrete Laplacian
       to the original image, and is a	less  extreme  high-pass  filter  than

       Edge, edge2, and	edge3 detect edges in various ways.  Edge examines the
       3x3 region surrounding each input pixel,	outputting 8 times the	center
       value minus the sum of its eight	neighbors.

       Edge2 applies a Sobel operator to the input image.  It approximates the
       image's gradient	by finite differences  on  a  3x3  neighborhood,  out-
       putting the vector length of the	gradient approximation.

       Edge3  likewise approximates the	gradient of the	input image.  The out-
       put is roughly the phase	angle of the  gradient	approximation,	scaled
       between 0 and 255.

       Extremum	 examines  the	3x3  region surrounding	each input pixel, out-
       putting the value that differs most from	the center value.  In case  of
       a tie, the larger candidate is chosen.

       Median  does noise reduction by replacing each pixel of the input image
       by the median of	the 3x3	region surrounding it.

       Nonoise implements the Bayer-Powell noise reduction  filter.   It  com-
       putes  the  average  value  of the eight	neighbors of each pixel	of the
       input image, and	substitutes it for the pixel value if the  two	differ
       by more than 64.

       Smooth  low-pass	filters	its input image	by convolution with a Bartlett

       Shadepic	treats its input image as an array  of	elevations.   At  each
       pixel  it  approximates the normal vector to the	height-field by	finite
       differences on a	3x3 neighborhood and outputs 255 times its dot product
       with  the unit vector in	the light-source direction specified by	option
       -l (default 1,-1,1).  If	the dot	product	is negative, it	is clamped  at
       zero.  (This computation	is just	Lambertian diffuse reflection.)



       There are too many weird	wired-in sizes.



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