In this paper, a novel Adaptive Variable-Length Quantizer design is proposed and its application to predictive image coding is presented The new quantiser makes advantage of the fact that more than 80% of the prediction error data usually reside near the origin and hence can be coded with small number of bits. The remaining 20% of the prediction error data can be coded with larger number of bits which results in smaller file size and enhanced quality of the reconstructed image. The simulation results showed improvements in the peak signal to noise ratio at the expense of increased computational complexity. The improvements in the quality of the compressed images overweight the computational complexity of the model.
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