19 August 1993 Robust, high-fidelity coding technique based on entropy-biased ANN codebooks
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We investigate the use of a Differential Vector Quantizer (DVQ) architecture for the coding of digital images. An Artificial 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 first method, both the encoder and the decoder have multiple codebooks of different sizes. In the second, variable bit-rates are achieved by encoding using subsets of one fixed codebook. We compare the performance of these approaches under conditions of error-free and error-prone channels.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
James E. Fowler, James E. Fowler, Stanley C. Ahalt, Stanley C. Ahalt, } "Robust, high-fidelity coding technique based on entropy-biased ANN codebooks", Proc. SPIE 1966, Science of Artificial Neural Networks II, (19 August 1993); doi: 10.1117/12.152619; https://doi.org/10.1117/12.152619


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