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16 September 1992 Neural-network-based image compression using AMT DAP 610
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Abstract
An error-less image compression of complex images has been achieved using a massively parallel computer. The algorithm involves utilization of a multi-level hierarchical structure of Kohonen type self-organizing learning vector quantization. The compression ratio increases greatly if a small amount of error is tolerated by limiting the number of templates employed. Utilization of DAP 610 enables the processing of compression and reconstruction in very short time. A few cases of error-less compression of several images, as well as some examples which achieved higher compression ratios by allowing a reasonable amount of error, are shown and compared.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kwang-Shik Min and Hisook L. Min "Neural-network-based image compression using AMT DAP 610", Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); https://doi.org/10.1117/12.140016
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