Luminance-chrominance colour spaces
Categories: computer science colour
Luminance chrominance colour spaces consist of 3 components:
- Luminance contains the overall brightness of the image. It is a bit like a greyscale image - if you looked at just the luminance component it would look similar to a black and white photograph.
- Two chrominance components. These indicate the colour once the lightness component has been removed.
There are several colour spaces that work in this way. Pillow supports YCbCr and L*a*b.
The two chrominance components contain similar information to the hue and saturation components of HSL, but it is coded differently. For example, in L*a*b, the *a component represents the position of the colour between magenta and green, the *b component represents the position of the colour between yellow and blue.
Luminance chrominance colour spaces have several uses:
- Analogue television. Black and white television was first broadcast in the mid 1930s, but it was another 30 years before colour TV was introduced. To allow for both systems, colour TV was broadcast as luminance (the original B&W signal) and a separate chrominance signal containing the colour information (that B&W sets would not pick up).
- Image compression. The eye can detect luminance information at greater resolution than chrominance (due to there being more rod cells than cone sells in the retina). JPEG image compression, and some video compression systems, take advantage of that fact. They encode the image data in a luminance chrominance space, but subsample the chrominance data.
- CIELAB is a widely used device independent colour space that uses luminance and chrominance to accurately represent colours as they are perceived by the human eye.
See also
Join the PythonInformer Newsletter
Sign up using this form to receive an email when new content is added:
Popular tags
2d arrays abstract data type alignment and angle animation arc array arrays bar chart bar style behavioural pattern bezier curve built-in function callable object chain circle classes clipping close closure cmyk colour combinations comparison operator comprehension context context manager conversion count creational pattern data science data types decorator design pattern device space dictionary drawing duck typing efficiency ellipse else encryption enumerate fill filter font font style for loop formula function function composition function plot functools game development generativepy tutorial generator geometry gif global variable gradient greyscale higher order function hsl html image image processing imagesurface immutable object in operator index inner function input installing iter iterable iterator itertools join l system lambda function latex len lerp line line plot line style linear gradient linspace list list comprehension logical operator lru_cache magic method mandelbrot mandelbrot set map marker style matplotlib monad mutability named parameter numeric python numpy object open operator optimisation optional parameter or pandas partial application path pattern permutations pie chart pil pillow polygon pong positional parameter print product programming paradigms programming techniques pure function python standard library radial gradient range recipes rectangle recursion reduce regular polygon repeat rgb rotation roundrect scaling scatter plot scipy sector segment sequence setup shape singleton slice slicing sound spirograph sprite square str stream string stroke structural pattern subpath symmetric encryption template tex text text metrics tinkerbell fractal transform translation transparency triangle truthy value tuple turtle unpacking user space vectorisation webserver website while loop zip zip_longest
