I am reading about k means algorithm at this link.
At ln here author mentioned that Input color space is 16 million possible colors. How author came up with 16 million number here. Kindly explain.
Additionally at the end it is mentioned as below
Some detail is certainly lost in the rightmost panel, but the overall image is still easily recognizable. This image on the right achieves a compression factor of around 1 million! While this is an interesting application of k-means, there are certainly better way to compress information in images. But the example shows the power of thinking outside of the box with unsupervised methods like k-means.
How compression is done here as we are still using data of shape (273280, 3) after compression. How compression of 1 million is achieved.