A Two-phase Color Quantization Approach Based on Spectral Clustering
Wenbo Xu · 2007
Color quantization or color reduction is an important technique for image analysis and has been widely used in image segmentation,image compression and image recognition.Firstly,on bisecting K-means is used to quantize image roughly and then we refine the image by improved spectral clustering based weighted distance.The stability and quickness of bisecting K-means and adjustable weight make our approach an attractive one.Experimental results show that our approach performs better than octree algorithm in quantized quality and has a less computation complexity than K-means algorithm.For special image,which includes one important color but with only a few pixels,traditional approaches usually lose the important color,but our approach can deal with it by introducing the weight for distances between pixels.