Apply color transformations to images.
Transformation functions alter the values of pixels in the image. Unlike convolutions, transformation functions do not depend on the values of nearby pixels. The vImage transformation functions fall into four broad categories:
Gamma correction functions correct the brightness profile of an image by multiplying each pixel by the value of the function. Gamma correction prepares an image for display or printing on a particular device.
Lookup table functions are like the piecewise polynomial functions, but instead of applying a polynomial they use a lookup table that you supply.
Matrix multiplication functions have a variety of uses, such as to convert between color spaces (RGB and YUV, for example), change a color image to a grayscale one, and for “color twisting.”
Piecewise functions are similar to the gamma correction functions, but instead of applying a predefined gamma function they apply one or more polynomials that you supply. The number of polynomials must be an integer power of 2, and they must all be of the same order.
Transformation functions use a vImage buffer structure (
v—see Data Types and Constants) to receive and supply image data. This buffer contains a pointer to image data, the height and width (in pixels) of the image data, and the number of row bytes. You actually pass a pointer to a vImage buffer structure.
Some transformation functions “work in place”. That is, the source and destination images can occupy the same memory if the they are strictly aligned pixel for pixel. For these, you can can provide a pointer to the same vImage buffer structure for one of the source images and the destination image.