Self-adaptive color image quantization algorithm based on Fisher discrimination
Yanli Hou · Computer Engineering and Applications Journal · 2010
A self-adaptive color image quantization algorithm based on Fisher discrimination is studied.Firstlyt,he original image is quantized to 256 colors using the octree algorithm.Secondly,based on the quantitative relation of the NBS distance and the color difference of human visual,the initial clustering centers and number are determined automatically.Thirdly,a peer group corresponding to the initial clustering center is automatically achieved by using the Fisher discrimination.And then,a color image quantization effect is achieved.At lasts,imulations are performed on the presented algorithm,and the simulation result shows that the presented algorithm not only can solve the problem of giving the number of quantization in advance but also has better quantization effect than the octree algorithm and k-means algorithm with the same quantization number.