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To get colorful images of the set, the assignment of a color to each value of the number of executed iterations can be made using one of a variety of functions (linear, exponential, etc.). One practical way, without slowing down calculations, is to use the number of executed iterations as an entry to a palette initialized at startup.
For each pixel, the surrounding 8 pixels are compared to the color of the source pixel. Shapes are detected by checking for pixels of similar color according to a YUV threshold. hqx uses the YUV color space to calculate color differences, so that differences in brightness are weighted higher to order to mimic human perception. [2]
When this is the case, does not belong to the Mandelbrot set, and color the pixel according to the number of iterations used to find out. Otherwise, keep iterating up to a fixed number of steps, after which we decide that our parameter is "probably" in the Mandelbrot set, or at least very close to it, and color the pixel black.
This is the standard blend mode which uses the top layer alone, [3] without mixing its colors with the layer beneath it: [example needed] (,) =where a is the value of a color channel in the underlying layer, and b is that of the corresponding channel of the upper layer.
The salient difference between CRI and MI is the color space used to calculate the color difference, the one used in CRI being obsolete and not perceptually uniform. MI can be decomposed into MI vis and MI UV if only part of the spectrum is being considered. The numerical result can be interpreted by rounding into one of five letter categories: [6]
8-bit color, with three bits of red, three bits of green, and two bits of blue. In order to turn a true color 24-bit image into an 8-bit image, the image must go through a process called color quantization. Color quantization is the process of creating a color map for a less color dense image from a more dense image. [2]
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Equivalently, the size of the map selected should be equal to or larger than the ratio of source colors to target colors. For example, when quantizing a 24 bpp image to 15 bpp (256 colors per channel to 32 colors per channel), the smallest map one would choose would be 4×2, for the ratio of 8 (256:32).