Colour space transformations are frequently used in image processing, graphics and visualisation applications. In many cases, these transformations are complex non-linear functions, which prohibit their use in time-cr...
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Colour space transformations are frequently used in image processing, graphics and visualisation applications. In many cases, these transformations are complex non-linear functions, which prohibit their use in time-critical applications. A new approach called minimax approximations for colour space transformations (MACT) is presented. The authors demonstrate MACT on three commonly used colour space transformations. Extensive experiments on a large and diverse image set and comparisons with well-known multidimensional look-up table interpolation methods show that MACT achieves an excellent balance among four criteria: ease of implementation, memory usage, accuracy and computational speed.
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