A Co-evolutionary Competitive Multi-expert Approach to Image Compression with Neural Networks

Bottle-neck MLP neural networks have been used in image compression and a few methods are developed to increase the compression quality. In this paper, a new co-evolutionary method is proposed to further improve the compression efficiency. A heterogeneous set of networks co-evolve and compete to compress different parts of an image with different characteristics. The results indicate a great improvement over the non-evolving methods