Abstract

Picture compression algorithms, using a parallel structure of neural networks, have recently been described. Although these algorithms are intrinsically robust, and may therefore be used in high noise environments, they suffer from several drawbacks: high computational complexity, moderate reconstructed picture qualities, and a variable bit-rate. In this paper, we describe a simple parallel structure in which all three drawbacks are eliminated: the computational complexity is low, the quality of the decompressed picture is high, and the bit-rate is fixed.

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