计算机工程 ›› 2011, Vol. 37 ›› Issue (23): 203-204,210.doi: 10.3969/j.issn.1000-3428.2011.23.069

• 图形图像处理 • 上一篇    下一篇

基于Y-H模型的奇异值分解图像压缩方法

丁立军1,华 亮2,冯 浩1   

  1. (1. 嘉兴学院机电工程学院,浙江 嘉兴 314001;2. 南通大学电气工程学院,江苏 南通 226019)
  • 收稿日期:2011-06-28 出版日期:2011-12-05 发布日期:2011-12-05
  • 作者简介:丁立军(1979-),男,讲师、博士研究生,主研方向:图像处理,模式识别;华 亮,讲师、博士研究生;冯 浩,教授、博士
  • 基金项目:
    国家自然科学基金资助项目(60871093)

Image Compression Method for Singular Value Decomposition Based on Y-H Model

DING Li-jun 1, HUA Liang 2, FENG Hao 1   

  1. (1. Mechanical & Electrical Engineering College, Jiaxing University, Jiaxing 314001, China; 2. School of Electrical Engineering, Nantong University, Nantong 226019, China)
  • Received:2011-06-28 Online:2011-12-05 Published:2011-12-05

摘要: 彩色图像在压缩时需要保存通道间的关联信息。针对该情况,提出一种基于Young-Helmholtz模型的奇异值分解(YH-SVD)图像压缩方法。证明YH-SVD的存在性,求得其结构形式,使用Greaves对Young-Helmholtz模型进行变换,由此进行图像压缩。实验结果表明,利用该方法能获得清晰的重构图像,峰值信噪比较高。

关键词: Young-Helmholtz模型, 奇异值分解, 彩色图像压缩, Greaves变换

Abstract: It is required to preserve the relativity information of each channel for color image when it is compressed. This paper proposes a compression method based on a new style of Singular Value Decomposition(SVD) founded on Young-Helmholtz model——YH-SVD. It proofs the existence and gives out the structural style of YH-SVD, and applies this method to compress color image after it is transformed into Greaves space. Experimental results show that this method can keep the clearness of reconstructed image, and can achieve high Peak Signal to Noise Ratio(PSNR).

Key words: Young-Helmholtz(Y-H) model, Singular Value Decomposition(SVD), color image compression, Greaves transformation

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