---

The Region of Interest

Although not explicitly labeled in Figure 1-6, the shaded area in each of the source images is the region of interest for samplers depicted in the figure. The region of interest, or ROI, defines the area in the source from which a sampler takes pixel information to provide to the kernel for processing. If you are a filter client, you don’t need to concern yourself with the ROI. But if you are a filter creator, you’ll want to understand the relationship between the region of interest and the domain of definition.

Recall that the domain of definition describes the bounding shape of a filter. In theory, this shape can be without bounds. Consider, for example, a filter that creates a repeating pattern that could extend to infinity.

The ROI and the domain of definition can relate to each other in the following ways:

• They coincide exactly—there is a 1:1 mapping between source and destination. For example, a hue filter processes a pixel from the working space coordinate (r,s) in the ROI to produce a pixel at the working space coordinate (r,s) in the domain of definition.

• They are dependent on each other, but modulated in some way. Some of the most interesting filters—blur and distortion, for example—use many source pixels in the calculation of one destination pixel. For example, a distortion filter might use a pixel (r,s) and its neighbors from the working coordinate space in the ROI to produce a single pixel (r,s) in the domain of definition.

• The domain of definition is calculated from values in a lookup table that are provided by the sampler. The location of values in the map or table are unrelated to the working space coordinates in the source image and the destination. A value located at (r,s) in a shading image does not need to be the value that produces a pixel at the working space coordinate (r,s) in the domain of definition. Many filters use values provided in a shading image or lookup table in combination with an image source. For example, a color ramp or a table that approximates a function, such as the arcsin function, provides values that are unrelated to the notion of working coordinates.

Unless otherwise instructed, Core Image assumes that the ROI and the domain of definition coincide. If you write a filter for which this assumption doesn’t hold, you need to provide Core Image with a routine that calculates the ROI for a particular sampler.

See “Supplying an ROI Function” for more information.

---