Joint source-channel fractal image coding with unequal error protection

We propose a joint source-channel coding system for fractal image compression. We allocate the available total bit rate between the source code and the channel code using a Lagrange multiplier optimization technique. The principle of the proposed unequal error protection strategy is to partition the information bits into sensitivity classes and to assign one code from a range of error-correcting codes to each sensitivity class in a nearly optimal way. Experimental results show that joint source-channel coding with fractal image compression is feasible, leads to efficient protection strategies, and outperforms previous works in this field that covered only channel coding with a fixed source rate.