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Here is a chart of all possible values for a different 8-bit float with 1 sign bit, 3 exponent bits and 4 significand bits. Having 1 more significand bit than exponent bits ensures that the precision remains at least 0.5 throughout the entire range. [6]
An 8-bit register can store 2 8 different values. The range of integer values that can be stored in 8 bits depends on the integer representation used. With the two most common representations, the range is 0 through 255 (2 8 − 1) for representation as an binary number, and −128 (−1 × 2 7) through 127 (2 7 − 1) for representation as two's complement.
24 bits almost always use 8 bits each of R, G, and B (8 bpc). As of 2018, 24-bit color depth is used by virtually every computer and phone display [citation needed] and the vast majority of image storage formats. Almost all cases of 32 bits per pixel assigns 24 bits to the color, and the remaining 8 are the alpha channel or unused.
The Tiki 100 uses an 8-bit RGB palette (also described as 3-3-2 bit RGB), with 3 bits for each of the red and green color components, and 2 bits for the blue component. It supports 3 different resolutions with 256, 512 or 1024 by 256 pixels and 16, 4, or 2 colors respectively (freely selectable from the full 256-color palette).
Similar binary floating-point formats can be defined for computers. There is a number of such schemes, the most popular has been defined by Institute of Electrical and Electronics Engineers (IEEE). The IEEE 754-2008 standard specification defines a 64 bit floating-point format with: an 11-bit binary exponent, using "excess-1023" format.
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.
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JPEG supports bit depths of 8 and 12 bits; JPEG XR supports bit depths of up to 32 bits. JPEG XR also supports lossless and lossy compression of floating-point image data (by representing the floating-point values in an IEEE 754-like format, and encoding them as though they were integers) and RGBE imagery.