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Relative luminance follows the photometric definition of luminance including spectral weighting for human vision, but while luminance is a measure of light in units such as /, relative luminance values are normalized as 0.0 to 1.0 (or 1 to 100), with 1.0 (or 100) being a theoretical perfect reflector of 100% reference white. [1]
Often the term luminance is used for the relative luminance, Y/Y n, where Y n is the luminance of the reference white point. Luma (Y ′) The weighted sum of gamma-corrected R ′, G ′, and B ′ values, and used in Y ′ CbCr, for JPEG compression and video transmission. Brightness (or value)
The word was proposed to prevent confusion between luma as implemented in video engineering and relative luminance as used in color science (i.e. as defined by CIE). Relative luminance is formed as a weighted sum of linear RGB components, not gamma-compressed ones. Even so, luma is sometimes erroneously called luminance. [2]
A luminance meter is a device used in photometry that can measure the luminance in a particular direction and with a particular solid angle. The simplest devices measure the luminance in a single direction while imaging luminance meters measure luminance in a way similar to the way a digital camera records color images. [6]
A comparison between a typical normalized M cone's spectral sensitivity and the CIE 1931 luminosity function for a standard observer in photopic vision. In the CIE 1931 model, Y is the luminance, Z is quasi-equal to blue (of CIE RGB), and X is a mix of the three CIE RGB curves chosen to be nonnegative (see § Definition of the CIE XYZ color space).
Chromaticity is an objective specification of the quality of a color regardless of its luminance. Chromaticity consists of two independent parameters , often specified as hue ( h ) and colorfulness ( s ), where the latter is alternatively called saturation , chroma , intensity , [ 1 ] or excitation purity .
A common strategy is to use the principles of photometry or, more broadly, colorimetry to calculate the grayscale values (in the target grayscale colorspace) so as to have the same luminance (technically relative luminance) as the original color image (according to its colorspace).
Color normalization is a topic in computer vision concerned with artificial color vision and object recognition. In general, the distribution of color values in an image depends on the illumination, which may vary depending on lighting conditions, cameras, and other factors.