1, with any fractional value in between. This representation is used in theoretical analyses, and in systems that use floating point representations. Each color component value can also be written as a percentage, from 0% to 100%. In computers, the component values are often stored as unsigned integer numbers in the range 0 to 255, the range that a single 8-bit byte can offer. These are often represented as either decimal or hexadecimal numbers. High-end digital image equipment are often able to deal with larger integer ranges for each primary color, such as 0..1023 (10 bits), 0..65535 (16 bits) or even larger, by extending the 24-bits (three 8-bit values) to 32-bit, 48-bit, or 64-bit units (more or less independent from the particular computer's word size). For example, brightest saturated red is written in the different RGB notations as: {| class="wikitable" ! Notation ! RGB triplet |- | Arithmetic | (1.0, 0.0, 0.0) |- | Percentage | (100%, 0%, 0%) |- | Digital 8-bit per channel | (255, 0, 0) #FF0000 (hexadecimal) |- | Digital 12-bit per channel | (4095, 0, 0) #FFF000000 |- | Digital 16-bit per channel | (65535, 0, 0) #FFFF00000000 |- | Digital 24-bit per channel | (16777215, 0, 0) #FFFFFF000000000000 |- | Digital 32-bit per channel | (4294967295, 0, 0) #FFFFFFFF0000000000000000 |} In many environments, the component values within the ranges are not managed as linear (that is, the numbers are nonlinearly related to the intensities that they represent), as in digital cameras and TV broadcasting and receiving due to gamma correction, for example. Linear and nonlinear transformations are often dealt with via digital image processing. Representations with only 8 bits per component are considered sufficient if gamma correction is used. Following is the mathematical relationship between RGB space to HSI space (hue, saturation, and intensity: HSI color space): If , then . Color depth The RGB color model is one of the most common ways to encode color in computing, and several different digital representations are in use. The main characteristic of all of them is the quantization of the possible values per component (technically a sample ) by using only integer numbers within some range, usually from 0 to some power of two minus one (2n − 1) to fit them into some bit groupings. Encodings of 1, 2, 4, 5, 8 and 16 bits per color are commonly found; the total number of