Hung A C, Tsern E K, Meng T H
InterVideo Inc., Fremont, CA 94539, USA.
IEEE Trans Image Process. 1998;7(10):1373-86. doi: 10.1109/83.718479.
Pyramid vector quantization (PVQ) uses the lattice points of a pyramidal shape in multidimensional space as the quantizer codebook. It is a fixed-rate quantization technique that can be used for the compression of Laplacian-like sources arising from transform and subband image coding, where its performance approaches the optimal entropy-coded scalar quantizer without the necessity of variable length codes. In this paper, we investigate the use of PVQ for compressed image transmission over noisy channels, where the fixed-rate quantization reduces the susceptibility to bit-error corruption. We propose a new method of deriving the indices of the lattice points of the multidimensional pyramid and describe how these techniques can also improve the channel noise immunity of general symmetric lattice quantizers. Our new indexing scheme improves channel robustness by up to 3 dB over previous indexing methods, and can be performed with similar computational cost. The final fixed-rate coding algorithm surpasses the performance of typical Joint Photographic Experts Group (JPEG) implementations and exhibits much greater error resilience.
金字塔向量量化（PVQ）使用多维空间中金字塔形状的格点作为量化器码本。它是一种固定速率量化技术，可用于压缩变换和子带图像编码中产生的类似拉普拉斯源，其性能接近最优熵编码标量量化器，而无需可变长度码。在本文中，我们研究了PVQ在有噪声信道上进行压缩图像传输的应用，其中固定速率量化降低了对误码损坏的敏感性。我们提出了一种推导多维金字塔格点索引的新方法，并描述了这些技术如何还能提高一般对称格点量化器的信道抗噪声能力。我们的新索引方案比以前的索引方法将信道鲁棒性提高了多达3 dB，并且可以以类似的计算成本执行。最终的固定速率编码算法超过了典型的联合图像专家组（JPEG）实现的性能，并表现出更强的抗误码能力。
