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pmid: 22562763
Pulse-code modulation (PCM) with embedded quantization allows the rate of the PCM bitstream to be reduced by simply removing a fixed number of least significant bits from each codeword. Although this source coding technique is extremely simple, it has a poor coding efficiency. In this paper, we present a generalized PCM (GPCM) algorithm for images that simply removes bits from each codeword. In contrast to PCM, however, the number and the specific bits that a GPCM encoder removes in each codeword depends on its position in the bitstream and the statistics of the image. Since GPCM allows the encoding to be performed with different degrees of computational complexity, it can adapt to the computational resources that are available in each application. Experimental results show that GPCM outperforms PCM with a gain that depends on the rate, the computational complexity of the encoding, and the degree of inter-pixel correlation of the image.
Pulse-code modulation, Reproducibility of Results, Binning, Signal Processing, Computer-Assisted, Data Compression, Image Enhancement, Sensitivity and Specificity, Interpolative coding, Pattern Recognition, Automated, Quantization, TEORIA DE LA SEÑAL Y COMUNICACIONES, Image Interpretation, Computer-Assisted, Algorithms
Pulse-code modulation, Reproducibility of Results, Binning, Signal Processing, Computer-Assisted, Data Compression, Image Enhancement, Sensitivity and Specificity, Interpolative coding, Pattern Recognition, Automated, Quantization, TEORIA DE LA SEÑAL Y COMUNICACIONES, Image Interpretation, Computer-Assisted, Algorithms
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