See: Description
| Class | Description |
|---|---|
| SoColorAntialiasingProcessing2d |
SoColorAntialiasingProcessing2d engine
The SoColorAntialiasingProcessing2d engine reduces the color artifacts. |
| SoColorGetPlaneProcessing2d |
SoColorGetPlaneProcessing2d engine
For an introduction to color transforms, see section Color Transforms. |
| SoColorSpaceConversionProcessing |
SoColorSpaceConversionProcessing engine
For an introduction to color transforms, see section Color Transforms. |
| SoColorToGrayscaleProcessing |
SoColorToGrayscaleProcessing engine
For an introduction to color transforms, see section Color Transforms. |
| SoColorToLightnessProcessing |
SoColorToLightnessProcessing engine
For an introduction to color transforms, see section Color Transforms. |
| SoDecorrelationStretchProcessing2d |
SoDecorrelationStretchProcessing2d engine
The SoDecorrelationStretchProcessing2d engine enhances the color differences found in a color image. |
| SoGrayscaleToColorProcessing |
SoGrayscaleToColorProcessing engine
For an introduction to color transforms, see section Color Transforms. |
| Enum | Description |
|---|---|
| SoColorSpaceConversionProcessing.BaseModes |
Color images usually are designated as RGB, HLS, or YIQ format. An RGB image is composed of three components, the red, green and blue channels.
Although the RGB basis is good for acquisition and display of color images, it is not always a good basis to explain the perception of colors.
An HLS image is composed of components expressing the hue, luminance and saturation. Hue refers to the color (red, orange, yellow, green, blue, purple). Saturation measures the lack of whiteness in a color ("fire engine" is satured red and pink is desatured). Luminance is an intensity measure and allows you to distinguish between light and dark.
The YIQ format is used largely in broadcasting. The advantage of YIQ images is that the brightness component Y can be used alone by monochrome receivers, while still spanning the color space with the chromatic components I and Q. In YIQ, the rgb basis is obtained by normalizing the RGB components so that
. It removes intensity information, making it easier to localize an area based on chromaticity or saturation information.
Most of the functions that works on gray level images will work on color images. The process is performed three times, once on each component. Be aware that YIQ images are floating point images.
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