Main Content

raw2planar

Separate Bayer pattern Color Filter Array (CFA) image into sensor element images

    Description

    example

    I = raw2planar(cfa) separates the channels of the Bayer pattern CFA image cfa into a multidimensional image, I, with a channel for each individual sensor element.

    Examples

    collapse all

    Read a Color Filter Array (CFA) image into the workspace. The rawread function returns cfa, a 4012-by-6034 image.

    cfa = rawread("colorCheckerTestImage.NEF");

    Split the returned CFA image into several individual images, each representing a CFA sensor component. The CFA image has a Bayer pattern of RGGB. The raw2planar function returns 2206-by-3017-by-4 array representing each component of the RGGB pattern.

    rggb = raw2planar(cfa);

    Input Arguments

    collapse all

    Bayer pattern CFA image, specified as an M-by-N numeric matrix.

    Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

    Output Arguments

    collapse all

    Image with a channel for each sensor element, returned as an (M/2)-by-(N/2)-by-4 numeric array of the same class as cfa.

    The order of the channels in the output image depends on the Bayer pattern of the CFA: the order of the red, green, and blue sensors. The 2-by-2 grid of pixels in the upper-left corner of the CFA image describes the channel order, from left-to-right, top-to-bottom. I(:,:,1) corresponds to the sensor at cfa(1,1), I(:,:,2) to the sensor at cfa(1,2), I(:,:,3) to the sensor at cfa(2,1), and I(:,:,4) to the sensor at cfa(2,2).

    Introduced in R2021a