Supported color formats

RGB

The RGB color model uses 3 colors: Red, Green, and Blue to construct all the colors. Each parameter in this format represents the intensity of the colors, expressed on a scale dependent on its bit depth.

Table 2 RGB pixel formats

Name

VL42 Identifier

RGB332

V4L2_PIX_FMT_RGB332

ARGB444

V4L2_PIX_FMT_ARGB444

RGBA444

V4L2_PIX_FMT_RGBA444

ABGR444

V4L2_PIX_FMT_ABGR444

BGRA444

V4L2_PIX_FMT_BGRA444

ARGB555

V4L2_PIX_FMT_ARGB555

RGBA555

V4L2_PIX_FMT_RGBA555

ABGR555

V4L2_PIX_FMT_ABGR555

BGRA555

V4L2_PIX_FMT_BGRA555

RGB565

V4L2_PIX_FMT_RGB565

BGR24

V4L2_PIX_FMT_BGR24

RGB24

V4L2_PIX_FMT_RGB24

ABGR32

V4L2_PIX_FMT_ABGR32

BGRA32

V4L2_PIX_FMT_BGRA32

RGBA32

V4L2_PIX_FMT_RGBA32

ARGB32

V4L2_PIX_FMT_ARGB32

YUV

The YUV color model consists of 3 elements:

  • Y is the brightness or luminescence information

  • U is the red color (chroma) difference value

  • V is the blue color (chroma) difference value

Both color difference values can be calculated by subtracting the Y value from the RGB color space’s blue component (for U) or red component (for V). Raviewer uses the following formulas to calculate each of the YUV values:

Y = R * .299000 + G * .587000 + B * .114000

U = R * -.168736 + G * -.331264 + B * .500000 + 128

V = R * .500000 + G * -.418688 + B * -.081312 + 128

Table 3 YUV pixel formats

Name

VL42 Identifier

Pixel plane

UYVY

V4L2_PIX_FMT_UYVY

PACKED

YUYV

V4L2_PIX_FMT_YUYV

PACKED

VYUY

V4L2_PIX_FMT_VYUY

PACKED

YVYU

V4L2_PIX_FMT_YVYU

PACKED

NV12

V4L2_PIX_FMT_NV12

SEMI-PLANAR

NV21

V4L2_PIX_FMT_NV21

SEMI-PLANAR

I420

V4L2_PIX_FMT_YUV420

PLANAR

YV12

V4L2_PIX_FMT_YVU420

PLANAR

I422

V4L2_PIX_FMT_YUV422P

PLANAR

Bayer RGB

Bayer format is a raw video format produced by image sensors that include a Bayer filter. A Bayer filter is a color filter array in which RGB color filters are arranged on a grid of square photosensors. A Bayer filter uses two green filter elements for each red and blue filter element. The filter array can be arranged in 4 distinct patterns. Their names are derived from the order of the filters in a single 2x2 pixel square:

Bayer pattern examples

Bayer format is a popular raw image format used in many modern color image sensors.

Table 4 Bayer RGB pixel formats

Name

VL42 Identifier

RGGB

V4L2_PIX_FMT_SRGGB8

RG10

V4L2_PIX_FMT_SRGGB10

RG12

V4L2_PIX_FMT_SRGGB12

RG16

V4L2_PIX_FMT_SRGGB16

Grayscale

In the grayscale color format, each pixel only conveys intensity information. This information can be expressed on a scale dependent on its bit depth, where the minimum value represents white, and the maximum value represents black.

Table 5 Grayscale pixel formats

Name

VL42 Identifier

GRAY

V4L2_PIX_FMT_GRAY

GRAY10

V4L2_PIX_FMT_Y10

GRAY12

V4L2_PIX_FMT_Y12

Adding new color formats

Currently, two classes can be used to describe color formats: ColorFormat and SubsampledColorFormat (found in app/image/color_format.py). To create a new color format:

  1. In color_format.py, add a new instance of one of the color format classes with the appropriate fields filled in under the AVAILABLE_FORMATS list.

  2. Add parsing and displaying functions to the AbstractParser in common.py.You can also use other parsers from the folder or implement a new one.

  3. The utility provides a proper parser by checking color format parameters (mainly PixelFormat) so make sure that your new color format has a valid translation of parameters to one of the parsers (you can find this functionality in app/parser/factory.py).

Note

Keep in mind that if you choose to implement a new parser, remember that parse() should return a one-dimensional ndarray with values read from the binary file, while display() should return an RGB-formatted 3-dimensional ndarray consisting of original color format values converted to RGB24.

Last update: 2024-12-25