An adaptive codebook design using the branching competitive learning network

This paper presents an adaptive scheme for codebook design by using a self-creating neural network, called branching competitive learning network. In our scheme, not only codevectors, but also codebook size are adaptively modified according to input image data and a distortion tolerance. In the situation that the input image is visually simple or the image data have a centralized distribution, our codebook design algorithm will assign a relatively small codebook; and for a complex image, our algorithm will give a relatively large codebook. Experimental results are given to illustrate the adaptability and effectiveness of our scheme