Sample Code

Real-Time Video Effects with vImage

Use vImage to apply effects to a video feed in real time.



This sample builds on the Converting Luminance and Chrominance Planes to an ARGB Image sample to leverage the lower-level, high-performance YpCbCr to RGB conversion functions provided by vImage to add additional, real-time video effects to a live camera stream.

Two effects are implemented in the YpCbCr color space:

  • Saturation Adjustment.

  • Dithering.

Two effects are implemented in the RGB color space:

  • Rotation.

  • Color quantization using lookup tables.

Saturation Adjustment

Screenshot of sample code app showing desaturated image.

You can easily adjust the color saturation of a YpCbCr image, without affecting its luminance, using the following formula:

Screenshot of saturation adjustment formula: Cbʹ = ((Cb - 128) * saturation) + 128.  Crʹ = ((Cr - 128) * saturation) + 128.

You use the vImageMatrixMultiply_Planar8 function to perform this math on the source chrominance buffer. The following code prepares the source chrominance buffer—which contains two planes for Cb and Cr—for use as the source and destination of the matrix multiply function:

let chromaBufferPointer = withUnsafePointer(to: &sourceChromaBuffer) {
    return $0

var sources: UnsafePointer<vImage_Buffer>? = chromaBufferPointer
var destinations: UnsafePointer<vImage_Buffer>? = chromaBufferPointer

Pass the pre-bias (–128), and then multiply by the divisor both the post-bias (+128) and the saturation. The saturation is passed to the matrix multiply function as a single element matrix:

var preBias: Int16 = -128
let divisor: Int32 = 0x1000
var postBias: Int32 = 128 * divisor

let saturation = mode == .dither ? 0 : fxValue

var matrix = [ Int16(saturation * Float(divisor)) ]

With the parameters prepared, call vImageMatrixMultiply_Planar8 to perform the saturation adjustment formula to the chrominance planes:


Apply Dithering

Screenshot of sample code app showing dithered image.

In this sample, dithering is applied only to the luminance channel: converting the grayscale image to a pattern of black dots. To eliminate the chrominance information, the dithering step uses the previous saturation adjustment step, with the saturation set to zero.

vImage provides dithering when reducing the bit depth of an image. In this sample, you convert the 8-bit luminance channel to a dithered 1-bit image, and then convert that back to 8-bit to pass to the YpCbCr to RGB function.

To create the 1-bit buffer, you initialize a vImage_Buffer structure, specifying one bit per pixel:

var ditheredLuma = vImage_Buffer()

vImage offers several dithering algorithms, this sample uses Atkinson dithering that’s specified by passing kvImageConvert_DitherAtkinson to the 8-bit to 1-bit conversion function. Because the luminance buffer is planar, use vImageConvert_Planar8toPlanar1 to do the conversion:


With ditheredLuma populated with the 1-bit dithered image, convert it back to 8-bit, specifying the original 8-bit luminance buffer, sourceLumaBuffer, as the destination:


Once you’re finished with the 1-bit planar buffer, free its memory:


Rotate the Image

Screenshot of sample code app showing rotated image.

vImage supports two types of specialized rotation functions—those that rotate an image in discrete 90º steps and those that rotate an image by an arbitrary angle. This sample uses the latter and specifies opaque white as the background color. Define the rotation, in radians, with the fxValue floating point variable::

let backcolor: [UInt8] = [255, 255, 255, 255]

Quantize Color Using Lookup Tables

Screenshot of sample code app showing color quantized image.

Mapping the individual channel values of an 8-bit per-channel image to a reduced set of values (for example, mapping the range 0…255 to the values [0, 25, 50, 75, 100, 125, 150, 175, 200, 225, 255]) decreases the number of distinct colors in an image. This process is known as color quantization and can be used for special effects or other applications such as compression.

vImage includes lookup table functions that provide this functionality. In this sample, generate the look up table dynamically based on a quantizationLevel value:

var lookUpTable = (0...255).map {
    return Pixel_8(($0 / quantizationLevel) * quantizationLevel)

With a quantizationLevel value of 25, lookUpTable contains 25 of each of the values in [0, 25, 50, 75, 100, 125, 150, 175, 200, 225, 255]. Passing lookupTable as the red, green, and blue lookup table parameters to vImageTableLookUp_ARGB8888 maps all of the red, green, and blue values between 0 and 24 to 0, between 25 and 49 to 25, between 50 and 74 to 50, and so on:


See Also

Core Video Interoperation

Reading From and Writing to Core Video Pixel Buffers

Transfer image data between Core Video pixel buffers and vImage buffers to integrate vImage operations into a Core Image workflow

Applying vImage Operations to Video Sample Buffers

Use vImage’s convert-any-to-any function to perform real-time image processing of video frames streamed from your device’s camera.

Core Video Interoperability

Pass image data between Core Video and vImage.