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- W2098916746 abstract "All kinds of compression coding system for digital images can be described by an universal approach while the digital image coding is regarded as pattern classification. According to it, a new coding system called the vector quantization with constraint is designed and implemented. The basic principle is that the coding is accomplished by quantization of vectors from small blocks consisting of nxn image elements. It is first performed to classify the vectors into a high level pattern class meaning a subspace in Hilbert space which represents inherent data structure of images, and then it is classified into a low-level pattern class by quantization of some parameters in the high-level pattern calss. The classifier design is based on the functional theory about Hilbert space. In order to reduce the degradation due to blocking effect, the system also uses a fine adaptive filter for post-processing. The experiment shows that this coding system can obtain satisfactory quality of the decoded image at 0.875 bit/pel bitrate and the coding speed is high due to the algorithm simplicity." @default.
- W2098916746 created "2016-06-24" @default.
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- W2098916746 date "2005-08-24" @default.
- W2098916746 modified "2023-09-25" @default.
- W2098916746 title "Digital image coding system using pattern recognition" @default.
- W2098916746 cites W3151726834 @default.
- W2098916746 doi "https://doi.org/10.1109/icsmc.1988.754262" @default.
- W2098916746 hasPublicationYear "2005" @default.
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