Rg chromaticity
The RGB chromaticity space, two dimensions of the normalized RGB space,
is a chromaticity space, a two-dimensional color space in which there is no intensity information.
In the RGB color space a pixel is identified by the intensity of red, green, and blue primary colors. Therefore, a bright red can be represented as, while a dark red may be. In the normalized RGB space or RG space, a color is represented by the proportion of red, green, and blue in the color, rather than by the intensity of each. Since these proportions must always add up to a total of 1, we are able to quote just the red and green proportions of the color, and can calculate the blue value if necessary.
Conversion between RGB and RG Chromaticity
Given a color where R, G, B = linear intensity of red, green and blue, this can be converted to color where imply the proportion of red, green and blue in the original color:The sum of rgb will always equal one, because of this property the b dimension can be thrown away without causing any loss in information. The reverse conversion is not possible with only two dimensions, as the intensity information is lost during the conversion to rg chromaticity, e.g. has equal proportions of each color, but it is not possible to determine whether this corresponds to black, gray, or white. If R, G, B, is normalized to r, g, G color space the conversion can be computed by the following:
The conversion from rgG to RGB, is the same as the conversion from xyY to XYZ. The conversion requires at least some information relative to the intensity of the scene. For this reason if the G is preserved then the inverse is possible.
Version used in computer vision
Motivation
Computer vision algorithms tend to suffer from varying imaging conditions. To make more robust computer vision algorithms it is important to use a color invariant color space. Color invariant color spaces are desensitized to disturbances in the image. One common problem in computer vision is varying light source between multiple images and within a single image.The rg colorspace is used out of a desire for. For example, if a scene is lit by a spotlight, an object of a given color will change in apparent color as it moves across the scene. Where color is being used to track an object in an RGB image, this can cause problems. Removing the intensity component should keep the color constant.
Practice
In practice, computer vision uses an "incorrect" form of rg colorspace derived directly from gamma-corrected RGB, typically sRGB. As a result, full removal of intensity is not achieved and 3D objects still show some of fringing.rg color space
r, g, and b chromaticity coordinates are ratios of the one tristimulus value over the sum of all three tristimulus values. A neutral object infers equal values of red, green and blue stimulus. The lack of luminance information in rg prevents having more than 1 neutral point where all three coordinates are of equal value. The white point of the rg chromaticity diagram is defined by the point. The white point has one third red, one third green and the final third blue. On an rg chromaticity diagram the first quadrant where all values of r and g are positive forms a right triangle. With max r equals 1 unit along the x and max g equals 1 unit along the y axis. Connecting a line from the max r to max g from a straight line with slope of negative 1. Any sample that falls on this line has no blue. Moving along the line from max r to max g, shows a decrease in red and an increase of green in the sample, without blue changing. The further a sample moves from this line the more blue is present in the sample trying to be matched.CIE RGB
RGB is a color mixture system. Once the color matching function are determined the tristimulus values can be determined easily. Since standardization is required to compare results, CIE established standards to determine color matching function.- The reference stimuli must be monochromatic lights R, G, B. With wavelengths respectively.
- The basic stimulus is white with equal energy spectrum. Require a ratio of 1.000:4.5907:0.0601 to match white point.
An example of color matching function below. is any monochromatic. Any monochromatic can be matched by adding reference stimuli and. The test light is also to bright to account for this reference stimuli is added to the target to dull the saturation. Thus is negative. and can be defined as a vector in a three-dimensional space. This three-dimensional space is defined as the color space. Any color can be reached by matching a given amount of and.
The negative calls for color matching functions that are negative at certain wavelengths. This is evidence of why the color matching function appears to have negative tristimulus values.