{'fraction_non_alphanumeric': 0.012264150943396227, 'fraction_numerical': 0.013207547169811321, 'mean_word_length': 5.1686046511627906, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Faster color conversion via lookup table mesh dimension management

Converting images between color spaces is a computationally very demanding task. The conversion is based on lookup tables that have an output colorspace value defined for each node in a mesh that covers the input space. If the input color value to be converted is not a mesh node, the output is computed by interpolating values in the surrounding mesh nodes. For a three dimensional input space, such as the RGB, tetrahedral and trilinear interpolations are used. If the input space is four dimensional, quadrilinear interpolation is used. This paper discusses how to reduce the complexity of lookup table implementation by exploiting the relationships between input and output color space components and using moderate lookup table expansion to achieve significant speed advantage. For example, a CMYK to K conversion, commonly implemented using quadrilinear interpolation on a 9x9x9x9 mesh can be reduced to bilinear interpolation assuming the mesh can grow from 6561 nodes to 684288 nodes.