Optional arguments:

• precision: VipsPrecision, calculation accuracy
• layers: %gint, number of layers for approximation
• cluster: %gint, 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.

By default, precision is

VIPS_PRECISION_FLOAT. 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_INTEGER, then elements of mask are converted to integers before convolution, using rint(), and the output image always has the same VipsBandFormat as the input image.

For #VIPS_FORMAT_UCHAR images and #VIPS_PRECISION_INTEGER precision, vips_conv() uses a fast vector path based on half-float arithmetic. This can produce slightly different results. Disable the vector path with --vips-novector or VIPS_NOVECTOR or vips_vector_set_enabled().

If precision is #VIPS_PRECISION_APPROXIMATE then, like

VIPS_PRECISION_INTEGER, mask is converted to int before convolution, and

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.

See also: vips_convsep().

This method is not directly available to language bindings.