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Optimal quantization of true-color images in MacAdam uniform color space

机译:Macatam均匀颜色空间中真彩图像的最佳量化

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Optimal color quantization of true-color images is very important for various multimedia applications. We used MacAdam color space, where all color distances are Euclidean, to realize quantization girds that are optimal in respect to human vision. Simple fractionally-bilinear (FB) approximations are proposed for strictly non-linear MacAdam formulae that describe the transformation of usual color space to MacAdam space. Optimal coefficients of FB functions are found for the inner part of the color triangle. Using of FB functions gives the possibility to find explicit color quantization for true-color real-world images in MacAdam space. Both rectangular and hexagonal quantization grids were used in our experiments. Visual tests have shown that the quality of a true-color image displayed on the screen of computer monitor remained very high up to mesh sizes of 8-10 just noticeable differences. Color entropy of quantized images was in this case about 5-6. This means the possibility to compress their colors about 3 times with the help of standard statistical methods. More complicated compression methods that remove spatial correlation of the neighboring image pixels can be used to reach much higher compression ratios.
机译:真彩色图像的最佳颜色量化对于各种多媒体应用非常重要。我们使用了Macadam颜色空间,所有颜色距离都是欧几里德,以实现对人类视觉最佳的量化围绕。对于严格的非线性麦克猫公式提出了简单的分馏 - 双线性(FB)近似,该公式描述了通常的颜色空间转换到麦克地甘露径空间。找到FB功能的最佳系数,用于颜色三角形的内部。使用FB函数可以在Macadam空间中找到真实的真实世界图像的明确颜色量化。在我们的实验中使用矩形和六边形量化网格。视觉测试已经表明,计算机监视器屏幕上显示的真彩图像的质量仍然非常高达8-10的网格尺寸只是显着的差异。在这种情况下,量化图像的颜色熵大约为5-6。这意味着在标准统计方法的帮助下压缩其颜色约3次颜色。可以使用更复杂的压缩方法来消除相邻图像像素的空间相关性来达到更高的压缩比。

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