Distortion-rate models for entropy-coded lattice vector quantization
The increasing demand for real-time applications requires the use of variable-rate quantizers having good performance in the low bit rate domain. In order to minimize the complexity of quantization, as well as maintaining a reasonably high PSNR ratio, we propose to use an entropy-coded lattice vecto...
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container_title | IEEE transactions on image processing |
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creator | Raffy, P. Antonini, M. Barlaud, M. |
description | The increasing demand for real-time applications requires the use of variable-rate quantizers having good performance in the low bit rate domain. In order to minimize the complexity of quantization, as well as maintaining a reasonably high PSNR ratio, we propose to use an entropy-coded lattice vector quantizer (ECLVQ). These quantizers have proven to outperform the well-known EZW algorithm's performance in terms of rate-distortion tradeoff. We focus our attention on the modeling of the mean squared error (MSE) distortion and the prefix code rate for ECLVQ. First, we generalize the distortion model of Jeong and Gibson (1993) on fixed-rate cubic quantizers to lattices under a high rate assumption. Second, we derive new rate models for ECLVQ, efficient at low bit rates without any high rate assumptions. Simulation results prove the precision of our models. |
doi_str_mv | 10.1109/83.887969 |
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In order to minimize the complexity of quantization, as well as maintaining a reasonably high PSNR ratio, we propose to use an entropy-coded lattice vector quantizer (ECLVQ). These quantizers have proven to outperform the well-known EZW algorithm's performance in terms of rate-distortion tradeoff. We focus our attention on the modeling of the mean squared error (MSE) distortion and the prefix code rate for ECLVQ. First, we generalize the distortion model of Jeong and Gibson (1993) on fixed-rate cubic quantizers to lattices under a high rate assumption. Second, we derive new rate models for ECLVQ, efficient at low bit rates without any high rate assumptions. 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subjects | Applied sciences Bit rate Computational complexity Computer Science Computer simulation Counters Decoding Distortion Exact sciences and technology Filling Image coding Image Processing Information, signal and communications theory Lattices Mathematical analysis Permissible error PSNR Rate-distortion Signal processing Telecommunications and information theory Vector quantization Vectors (mathematics) |
title | Distortion-rate models for entropy-coded lattice vector quantization |
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