An effective codebook initialization technique for LBG algorithm using subtractive clustering

Vector quantization (VQ) is one of the lossy image compression techniques. VQ comprises of three different phases: codebook generation, image encoding and image decoding. The performance of VQ based image compression technique depends upon the constructed codebook. A widely used technique for VQ codebook design is the Linde-Buzo-Gray (LBG) algorithm. However the performance of the standard LBG algorithm is highly dependent on the choice of the initial codebook. In this paper, we have proposed a simple and very effective approach for codebook initialization for LBG algorithm. This method uses the subtractive clustering to generate initial codebook for LBG algorithm. Experimental results show that the proposed method gives less RMSE and higher PSNR as comparison to other tested methods, including the LBG and cluster density algorithms.