High Efficient Image Coding System Using Vector Quantization in Transform Domain

变换域矢量量化的高效图像编码系统

基本信息

批准号：
61460129
负责人：
HARASHIMA Hiroshi
金额：
$ 3.97万
依托单位：
The University of Tokyo
依托单位国家：
日本
项目类别：
Grant-in-Aid for General Scientific Research (B)
财政年份：
1986
资助国家：
日本
起止时间：
1986 至 1987
项目状态：
已结题

项目摘要

In this project, image coding schemes using vector quantization are systematically studied. The results of this research are as follows.(1)Consideration concerning Vector Quantization fo Picture SignalsTwo problems are pointed out in application of vector quantization. One is the complexity of vector quantizer and the other is robustness of vector quantizer performance.(2)Discrete Cosine Transform Coding with Vector Quantization (DCT-VQ)A new vector quantization scheme using discrete cosine transform, named DCT-VQ is proposed. To arrive at an universal vector quantizer, vector quantizers are designed for a standard probability distribution independent of picture signals. The complexity is greatly reduced because of a decomposition of transform domain into vectors.(3)Adaptive DCT-VQAdaptive DCT-VQ is presented, which employs adaptive control of coding parameters according to the local property of picture signals in order to improve the performance of DCT-VQ. The simulations have shown that the adaptive DCT-VQ outperforms the conventional adaptive transform codings. An application of this scheme to color image coder using color coordinate conversion is also presented.(4)Differential Vector QuantizationTo realize robust quantization, differential vector quantization is also proposed, which vector-quantizes predictive error signals using universal vector quantizer designed for standard distribution.(5)Fast Search Algorithms for Vector Quantization in orthogonal Transform DomainIn order to attain fast search at vector quantization, a partial distance algorithm and nearest-neighbor search algorithm are proposed, both in the orthogonal transform domain. These algorithms needs less multiplications than the tree-search algorithms for signal sources such as picture signals which have concentration in the transform domain power distribution.

在此项目中，系统地研究了使用矢量量化的图像编码方案。这项研究的结果如下。（1）在应用矢量量化时指出了有关矢量量化问题的考虑。一个是向量量化的复杂性，另一个是向量量化性能的鲁棒性。（2）使用离散余弦变换的新型矢量量化方案进行离散的余弦变换编码（DCT-VQ），提出了名为DCT-VQ的新矢量量化方案。为了获得通用矢量量化器，矢量量化器设计用于独立于图片信号的标准概率分布。由于将变换域分解为向量，因此大大降低了复杂性。（3）提出了自适应DCT-VQadaptive DCT-VQ，它根据图片信号的局部属性对编码参数采用自适应控制，以提高DCT-VQ的性能。模拟表明，自适应DCT-VQ优于常规自适应转换编码。 An application of this scheme to color image coder using color coordinate conversion is also presented.(4)Differential Vector QuantizationTo realize robust quantization, differential vector quantization is also proposed, which vector-quantizes predictive error signals using universal vector quantizer designed for standard distribution.(5)Fast Search Algorithms for Vector Quantization in orthogonal Transform DomainIn order to attain fast search at vector quantization, a partial distance algorithm and在正交转换域中提出了最近的邻居搜索算法。这些算法所需的乘法要比在转换域功率分布中浓度的摄影信号等信号源的树搜索算法所需的乘法更少。