彩色图像三维六边形离散余弦变换编码

王墨林; 莽思淋; 桑爱军; 崔海廷; 陈贺新

doi:10.3788/OPE.20132101.0217

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彩色图像三维六边形离散余弦变换编码

信息科学 | 更新时间：2020-08-12

- 彩色图像三维六边形离散余弦变换编码
- Three dimentional hexagonal discrete cosine transform for color image coding
- 光学精密工程 2013年21卷第1期页码：217-223
- 作者机构：
  
  吉林大学通信工程学院,吉林长春,中国,130012
- 作者简介：
- 基金信息：
  
  国家自然科学基金项目(51575523)
- DOI：10.3788/OPE.20132101.0217
  中图分类号： TP391.4
- 收稿日期：2012-06-19，
  
  修回日期：2012-09-13，
  
  网络出版日期：2013-01-24，
  
  纸质出版日期：2013-01-15
- 稿件说明：
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王墨林莽思淋桑爱军崔海廷陈贺新. 彩色图像三维六边形离散余弦变换编码[J]. 光学精密工程, 2013,21(1): 217-223

WANG Mo-lin MANG Si-lin SANG Ai-jun CUI Hai-ting CHEN He-xin. Three dimentional hexagonal discrete cosine transform for color image coding[J]. Editorial Office of Optics and Precision Engineering, 2013,21(1): 217-223
王墨林莽思淋桑爱军崔海廷陈贺新. 彩色图像三维六边形离散余弦变换编码[J]. 光学精密工程, 2013,21(1): 217-223 DOI： 10.3788/OPE.20132101.0217.

WANG Mo-lin MANG Si-lin SANG Ai-jun CUI Hai-ting CHEN He-xin. Three dimentional hexagonal discrete cosine transform for color image coding[J]. Editorial Office of Optics and Precision Engineering, 2013,21(1): 217-223 DOI： 10.3788/OPE.20132101.0217.

摘要

为了适应人眼视网膜细胞的正六边形结构的排列方式并充分利用彩色图像各颜色分量间的相关性，提出了一种基于六边形采样的三维离散余弦变换方法。该方法根据传统的矩形采样和正六边形采样之间的关系来完成两者的转换；然后在已有的六边形离散余弦变换的基础上提出三维六边形采样的离散余弦变换，并验证它的能量集中性。最后，在同一个模型下建立彩色图像的空间位置和颜色分量，并利用提出的方法分别以不同的子图大小对不同的图像进行整体变换。实验结果表明：相对于传统的矩形采样，提出方法的压缩比提高了约51.1%，峰值信噪比提高了约16.3%，从而有效地降低了彩色图像各颜色分量间的相关性。得到的结果表明，利用六边形采样技术可以提高采样率，降低编码速率。

Abstract

A three-dimensional(3D) Discrete Cosine Transform(DCT) method based on hexagonal sampling was proposed to fit the arrangement of hexagonal structure of the human retinal cells and to take advantage of the correlation among each color component of the color images. The method completed the conversion between the traditional rectangular sampling and hexagonal sampling according their relationships. Then

it proposed 3D Hexagonal sampling DCT(3D HDCT) on the basis of existing HDCT and verified its energy concentration. Finally

the spatial positions and color components of the color images in the same model were established

and the different images were transformed with different sub-plot sizes in a whole way by proposed method respectively. Experimental results show that the proposed method increases the compression ratio about 51.1% and the Peak Sigal to Noise Ratio (PSNR) about 16.3% as compared with that traditional rectangular sampling method

respectively. The results decrease the correlation among color components of color images effectively

and demonstrate that hexagonal sampling applied to image coding can improve sampling rates and decrease coding rates.

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references

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