Robust, High--delity Coding Technique Based on Entropy-biased Ann Codebooks

We investigate the use of a Diierential Vector Quantizer (DVQ) architecture for the coding of digital images. An Artiicial Neural Network (ANN) is used to develop entropy-biased codebooks which yield substantial data compression while retaining insensitivity to transmission channel errors. Two methods are presented for variable bit-rate coding using the described DVQ algorithm. In the rst method, both the encoder and the decoder have multiple codebooks of diierent sizes. In the second, variable bit-rates are achieved by encoding using subsets of one xed codebook. We compare the performance of these approaches under conditions of error-free and error-prone channels.