man(1) Manual page archive

     FILTERS(9.1)                                         FILTERS(9.1)

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

          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 7×7 region centered on each input pixel, remapping the
          center pixel linearly 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 17×17 region centered on each input pixel, counting the
          number of pixels whose value is less than the center pixel.
          (It counts ½ for each pixel equal to the center value.)
          Output pixel values are 255 times the count divided by the

     FILTERS(9.1)                                         FILTERS(9.1)

          window size.

          Crispen examines the 3×3 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 3×3
          discrete Laplacian to the original image, and is a less
          extreme high-pass filter than crispen.

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

          Edge2 applies a Sobel operator to the input image.  It
          approximates the image's gradient by finite differences on a
          3×3 neighborhood, outputting the vector length of the gradi-
          ent approximation.

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

          Extremum examines the 3×3 region surrounding each input
          pixel, outputting the value that differs most from the cen-
          ter value.  In case of a tie, the larger candidate is cho-

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

          Nonoise implements the Bayer-Powell noise reduction filter.
          It computes 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 window.

          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 3×3 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 reflec-


     FILTERS(9.1)                                         FILTERS(9.1)



          There are too many weird wired-in sizes.