Neural network approaches to fractal image compression and decompression

In image compression technologies, fractal image compression/decompression has the advantages of a high compression ratio and a low loss ratio. However, it requires a great deal of computation, which limits its applications, and so far, no parallel processing technique has been designed and implemented. In this study, we use neural networks to perform a large number of computations in fractal image compression and decompression in parallel. The simulation results show that the quality of images generated by neural networks is similar to that produced using traditional methods, which verifies the high value of our research, which has shown that the neural network technology is useful and efficient when applied to fractal image compression and decompression. (C) 2001 Elsevier Science B.V. All rights reserved.