4 ms·

Depends on exactly what "average" means in this context. The most naive of interpretations (e.g. averaging each of the R/G/B values) is generally not what we w

• rckoepke 6y ago
  I've done this exercise and generally what you want is a combination of your suggestion (which is elaborated by 'polyphora[0]) and 'p1necone's suggestion [1] Polyphora mentioned CIELAB as just one example, and it's a good example. I believe state of the art these days is Oklab[2], talked about here[3]. I'd like to pull out a comment from 'jiggawatts in that discussion: > This is a tour de force of colour theory, and should be mandatory reading for anyone serious about computer colour! I completely agree. With regards to 'p1necone's suggestion, k-nearest neighbors is one simple and relatively easy way to separate the colors into bins. I've only done this on a single image, but with multiple images maybe you could also k-nn bin the resulting colors from each image and only return bins which have multiple members. 0: https://news.ycombinator.com/item?id=25828733 https://news.ycombinator.com/item?id=25828733 1: https://news.ycombinator.com/item?id=25828773 https://news.ycombinator.com/item?id=25828773 2: https://bottosson.github.io/posts/oklab/ https://bottosson.github.io/posts/oklab/ 3: https://news.ycombinator.com/item?id=25525726 https://news.ycombinator.com/item?id=25525726