• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

一种用于图像矢量量化的复杂度降低技术。

A complexity reduction technique for image vector quantization.

机构信息

Dept. of Electron. Eng., City Polytech. of Hong Kong.

出版信息

IEEE Trans Image Process. 1992;1(3):312-21. doi: 10.1109/83.148605.

DOI:10.1109/83.148605
PMID:18296165
Abstract

A technique for reducing the complexity of spatial-domain image vector quantization (VQ) is proposed. The conventional spatial domain distortion measure is replaced by a transform domain subspace distortion measure. Due to the energy compaction properties of image transforms, the dimensionality of the subspace distortion measure can be reduced drastically without significantly affecting the performance of the new quantizer. A modified LBG algorithm incorporating the new distortion measure is proposed. Unlike conventional transform domain VQ, the codevector dimension is not reduced and a better image quality is guaranteed. The performance and design considerations of a real-time image encoder using the techniques are investigated. Compared with spatial domain a speed up in both codebook design time and search time is obtained for mean residual VQ, and the size of fast RAM is reduced by a factor of four. Degradation of image quality is less than 0.4 dB in PSNR.

摘要

提出了一种降低空域图像矢量量化(VQ)复杂度的技术。用变换域子空间失真测度取代传统的空域失真测度。由于图像变换的能量集中特性,在不显著影响新量化器性能的情况下,子空间失真测度的维数可以大大降低。提出了一种结合新失真测度的改进 LBG 算法。与传统的变换域 VQ 不同,码矢量维数没有减少,并且保证了更好的图像质量。研究了使用这些技术的实时图像编码器的性能和设计考虑因素。与空域相比,平均残差 VQ 的码本设计时间和搜索时间都得到了加快,快速 RAM 的大小减小了四倍。PSNR 中的图像质量下降小于 0.4dB。

相似文献

1
A complexity reduction technique for image vector quantization.一种用于图像矢量量化的复杂度降低技术。
IEEE Trans Image Process. 1992;1(3):312-21. doi: 10.1109/83.148605.
2
Image-adaptive vector quantization in an entropy-constrained framework.基于约束熵的图像自适应矢量量化。
IEEE Trans Image Process. 1997;6(3):441-50. doi: 10.1109/83.557354.
3
Predictive residual vector quantization [image coding].预测残差矢量量化 [图像编码]。
IEEE Trans Image Process. 1995;4(11):1482-95. doi: 10.1109/83.469930.
4
Multiplication free vector quantization using L(1) distortion measure and its variants.基于 L(1)失真测度及其变体的无乘法向量量化。
IEEE Trans Image Process. 1992;1(1):11-7. doi: 10.1109/83.128027.
5
On the Initialization of Swarm Intelligence Algorithms for Vector Quantization Codebook Design.用于矢量量化码本设计的群体智能算法初始化研究
Sensors (Basel). 2024 Apr 19;24(8):2606. doi: 10.3390/s24082606.
6
Reduced storage VQ via secondary quantization.通过二次量化减少存储向量量化
IEEE Trans Image Process. 1998;7(4):477-95. doi: 10.1109/83.663492.
7
Sequential scalar quantization of vectors: an analysis.向量的顺序标量量化:分析。
IEEE Trans Image Process. 1995;4(9):1282-95. doi: 10.1109/83.413172.
8
A fractal vector quantizer for image coding.用于图像编码的分形矢量量化器。
IEEE Trans Image Process. 1998;7(11):1598-602. doi: 10.1109/83.725366.
9
A comparison of several vector quantization codebook generation approaches.几种矢量量化码本生成方法的比较。
IEEE Trans Image Process. 1993;2(1):108-12. doi: 10.1109/83.210871.
10
Comments on "Modified K-means algorithm for vector quantizer design".关于《用于矢量量化器设计的改进K均值算法》的评论
IEEE Trans Image Process. 2000;9(11):1964-7. doi: 10.1109/83.877216.