vips_conv ()

int
vips_conv (VipsImage *in,
           VipsImage **out,
           VipsImage *mask,
           ...);

Optional arguments:

precision : calculation accuracy layers : number of layers for approximation cluster : cluster lines closer than this distance

Convolution.

Perform a convolution of in with mask . Each output pixel is calculated as sigma[i]{pixel[i] * mask[i]} / scale + offset, where scale and offset are part of mask .

If precision is VIPS_PRECISION_INTEGER then the convolution is performed with integer arithmetic and the output image always has the same VipsBandFormat as the input image.

Convolutions on unsigned 8-bit images are calculated with the processor's vector unit, if possible. Disable this with --vips-novector or IM_NOVECTOR.

If precision is VIPS_PRECISION_FLOAT then the convolution is performed with floating-point arithmetic. The output image is always VIPS_FORMAT_FLOAT unless in is VIPS_FORMAT_DOUBLE, in which case out is also VIPS_FORMAT_DOUBLE.

If precision is VIPS_PRECISION_APPROXIMATE then the output image always has the same VipsBandFormat as the input image.

Larger values for layers give more accurate results, but are slower. As layers approaches the mask radius, the accuracy will become close to exact convolution and the speed will drop to match. For many large masks, such as Gaussian, n_layers need be only 10% of this value and accuracy will still be good.

Smaller values of cluster will give more accurate results, but be slower and use more memory. 10% of the mask radius is a good rule of thumb.

vips_compass ()

int
vips_compass (VipsImage *in,
              VipsImage **out,
              VipsImage *mask,
              ...);

vips_convsep ()

int
vips_convsep (VipsImage *in,
              VipsImage **out,
              VipsImage *mask,
              ...);

Optional arguments:

precision : calculation accuracy layers : number of layers for approximation cluster : cluster lines closer than this distance

Perform a separable convolution of in with mask . See vips_conv() for a detailed description.

The mask must be 1xn or nx1 elements.

The image is convolved twice: once with mask and then again with mask rotated by 90 degrees. This is much faster for certain types of mask (gaussian blur, for example) than doing a full 2D convolution.

See also: vips_conv(), vips_gaussmat().

vips_sharpen ()

int
vips_sharpen (VipsImage *in,
              VipsImage **out,
              ...);

Optional arguments:

radius : how large a mask to use x1 : flat/jaggy threshold y2 : maximum amount of brightening y3 : maximum amount of darkening m1 : slope for flat areas m2 : slope for jaggy areas

Selectively sharpen the L channel of a LAB image. The input image is transformed to VIPS_INTERPRETATION_LABS.

The operation performs a gaussian blur of radius radius and subtracts from in to generate a high-frequency signal. This signal is passed through a lookup table formed from the five parameters and added back to in .

The lookup table is formed like this:

                     ^
                  y2 |- - - - - -----------
                     |         / 
                     |        / slope m2
                     |    .../    
             -x1     | ...   |    
 -------------------...---------------------->
             |   ... |      x1           
             |... slope m1
             /       |
            / m2     |
           /         |
          /          |
         /           |
        /            |
 ______/ _ _ _ _ _ _ | -y3
                     |

For printing, we recommend the following settings (the defaults):

  radius == 3
  x1 == 1.5
  y2 == 20         (don't brighten by more than 20 L*)
  y3 == 50         (can darken by up to 50 L*)

  m1 == 1          (some sharpening in flat areas)
  m2 == 2          (more sharpening in jaggy areas)

If you want more or less sharpening, we suggest you just change the m1 and m2 parameters.

The radius parameter changes the width of the fringe and can be adjusted according to the output printing resolution. As an approximate guideline, use 1 for 4 pixels/mm (CRT display resolution), 2 for 8 pixels/mm, 3 for 12 pixels/mm and 4 for 16 pixels/mm (300 dpi == 12 pixels/mm). These figures refer to the image raster, not the half-tone resolution.

See also: vips_conv().

vips_gaussblur ()

int
vips_gaussblur (VipsImage *in,
                VipsImage **out,
                double sigma,
                ...);

Optional arguments:

precision : VipsPrecision for blur, default VIPS_PRECISION_INTEGER min_ampl : minimum amplitude, default 0.2

This operator runs vips_gaussmat() and vips_convsep() for you on an image. Set min_ampl smaller to generate a larger, more accurate mask. Set sigma larger to make the blur more blurry.

See also: vips_gaussmat(), vips_convsep().

vips_spcor ()

int
vips_spcor (VipsImage *in,
            VipsImage *ref,
            VipsImage **out,
            ...);

Calculate a correlation surface.

ref is placed at every position in in and the correlation coefficient calculated. The output image is always float.

The output image is the same size as the input. Extra input edge pixels are made by copying the existing edges outwards.

The correlation coefficient is calculated as:

         sumij (ref(i,j)-mean(ref))(inkl(i,j)-mean(inkl))
c(k,l) = ------------------------------------------------
         sqrt(sumij (ref(i,j)-mean(ref))^2) *
                     sqrt(sumij (inkl(i,j)-mean(inkl))^2)

where inkl is the area of in centred at position (k,l).

from Niblack "An Introduction to Digital Image Processing", Prentice/Hall, pp 138.

If the number of bands differs, one of the images must have one band. In this case, an n-band image is formed from the one-band image by joining n copies of the one-band image together, and then the two n-band images are operated upon.

The output image is always float, unless either of the two inputs is double, in which case the output is also double.

See also: vips_fastcor().

vips_fastcor ()

int
vips_fastcor (VipsImage *in,
              VipsImage *ref,
              VipsImage **out,
              ...);

Calculate a fast correlation surface.

ref is placed at every position in in and the sum of squares of differences calculated.

The output image is the same size as the input. Extra input edge pixels are made by copying the existing edges outwards.

If the number of bands differs, one of the images must have one band. In this case, an n-band image is formed from the one-band image by joining n copies of the one-band image together, and then the two n-band images are operated upon.

The output type is uint if both inputs are integer, float if both are float or complex, and double if either is double or double complex. In other words, the output type is just large enough to hold the whole range of possible values.

See also: vips_spcor().

enum VipsCombine

How to combine values.