一种基于视觉感知的色彩量化算法

A Color Quantization Algorithm Based on Human Visual Perception

提出一种色彩量化算法.该算法将图像中的区域细分为边缘、内部平滑区域和内部纹理区域3个部分,并根据它们对视觉感知的重要程度赋予不同的量化权重,以达到强化视觉上相对重要的边缘和内部平滑区域、弱化视觉上相对不重要的复杂纹理区域的目的.另外,为了在量化效果和时间性能上取得折衷,对 HSV 色彩空间固定V值的蜂窝状分割量化算法进行改进,实现一种可在整个色彩空间完成动态分割的量化算法.在保证时间性能比原有算法略有改善的前提下,减少色彩量化的误差.实验结果表明,本文算法只需要为数较少的量化色彩就能达到较好的量化效果,特别适用于基于内容的图像检索等应用场合.

A color quantization algorithm is proposed in this paper. By this algorithm, an image is classified as edge, smooth and texture regions, and different weight strategies are assigned to them based on different degrees of perceptions. Thus, the relatively important perceptual regions, such as edge and smooth regions are strengthened and the relatively unimportant ones are weakened, such as complex texture regions. Moreover, to reach a compromise between color quantization results and time performance, the cellular color decomposition algorithm which fixes the V value is improved and the quantization algorithm is fulfilled, which could decompose the whole color space adaptively. The algorithm reduces the error of color quantization while the time performance is improved a little. The experimental results show that good quantization results are obtained by using a few colors. The proposed algorithm is especially suitable for content-based image retrieval.