结合Gamma修正的色彩量化新算法

色彩量化的最终目的是使得视觉效果上的最化图像与原图像的差别（即失真）最小，量化的应用又对算法效率提出很高的要求，文中提出一种结合Gamma修正的量化算法，速度明显快于中位切分等以往算法，并且量化图像的质量近似于，甚至部分视觉效果优于这些算法，该算法是一种切实有效的图像量化方法，它在计算复杂度和量人结果的精确度上进行了折衷。

Fast Color Quantization Algorithm Integrated with Gamma Correction

The ultimate goal of color image quantization is to minimize visible distortion. While the application of it as a frame buffer technique requires high efficiency of algorithm, a significantly faster quantization strategy than previous methods: median cut, variance, or octree based algorithms, etc., is suggested. The new algorithm is integrated with Gamma correction to partially compensate for perceptually uniform nature in RGB, its output result is approximately as accurate as previous methods. Overall, the new proposed method is a preferable tradeoff between the quantizer complexity and visible distortion in the quantized image.