一种新颖的图像多尺度几何变换及其应用

孙文方; 宋蓓蓓; 赵亦工

您当前的位置：

首页 >

文章列表页 >

一种新颖的图像多尺度几何变换及其应用

专题研究 | 更新时间：2025-12-08

- 一种新颖的图像多尺度几何变换及其应用
- Novel Image Multiscale Geometric Transform and Its Applications
- 西安交通大学学报 2007年41卷第8期页码：982-985
- 作者机构：
  
  西安电子科技大学电子工程学院,西安,710071
- 作者简介：
- 基金信息：
  
  : 2007-01-05. 作者简介: 孙文方(1979～),男,博士生;赵亦工(联系人),男,教授,博士生导师. 基金项目: 国家自然科学基金资助项目(60572151)
- DOI：
  中图分类号： TN911.7
- 网络首发：2007-08-10，
  
  纸质出版：2007
- 稿件说明：
移动端阅览
孙文方, 宋蓓蓓, 赵亦工. 一种新颖的图像多尺度几何变换及其应用[J]. 西安交通大学学报, 2007,41(8):982-985.

孙文方, 宋蓓蓓, 赵亦工. Novel Image Multiscale Geometric Transform and Its Applications[J]. 2007, 41(8): 982-985.
孙文方, 宋蓓蓓, 赵亦工. 一种新颖的图像多尺度几何变换及其应用[J]. 西安交通大学学报, 2007,41(8):982-985. DOI：

孙文方, 宋蓓蓓, 赵亦工. Novel Image Multiscale Geometric Transform and Its Applications[J]. 2007, 41(8): 982-985. DOI：

摘要

提出了一种新颖的图像多尺度几何变换方法

主要由预处理、方向滤波器组和最优方向小波变换等组成.方向滤波器组将预处理后的高频分量分解为多个方向子带

然后每个方向子带执行改进的最优方向小波变换.该变换兼有Bandelet变换和Contourlet变换的多尺度几何分析特性

能更稀疏地表示边缘和纹理特征.分别将EBCOT编码和硬阈值去噪应用到图像变换系数中

从而实现了有效的图像压缩和去噪

很好地保护了图像细节.实验结果表明

对于纹理和边缘丰富的图像

所提出的图像压缩和去噪方法在视觉质量上明显优于基于Bandelet或Contourlet变换的方法

峰值信噪比也提高了0.1 dB以上.

Abstract

A novel image multiscale geometric transform method is proposed. It is composed of pre-processing

directional filterbank and optimized directional wavelet transform. After pre-processing the image

the high frequency components are decomposed into several directional subbands by directional filterbank

and the modified optimized-directional wavelet transform is performed for each directional subband. The transform has the characteristics of multiscale geometric analysis of both Bandelet and Contourlet transforms

and it represents the edges and texture features more sparsely. The EBCOT coder and hard-threshold denoising are applied to the transform coefficients individually so as to realize efficient image compression and denoising and preserve the image details well. The experiments show that the proposed image compression and denoising method can significantly outperform those that are based on Bandelet or Contourlet transform in visual quality for the images with abundant edges and texture

and the peak signal to noise ratio is also increased by more than 0.1 dB.

关键词

Keywords

references

Do M N, Vetterli M. The contourlet transform: an efficient directional multiresolution image representation [J]. IEEE Trans on Image Proc, 2005,14(12): 2091-2106.

Lu Y, Do M N. CRISP-contourlets: a critically sampled directional multiresolution image representation [C]∥Proc SPIE Conf on Wavelets Ⅹ. San Diego, USA: SPIE, 2003: 655-665.

Le P E, Mallat S. Sparse geometric image representation with bandelets [J]. IEEE Trans on Image Proc, 2005,14(4): 423-438.

Peyre G, Mallat S. Surface compression with geometric bandelets [J]. ACM Trans on Graphics, 2005, 24(3): 601-608.

Bamberger R H, Smith M J T. A filter bank for the directional decomposition of images: theory and design [J]. IEEE Trans on Signal Proc, 1992, 40(4): 882-893.

Velisavljevic V, Beferull-Lozano B, Vetterli M, et al. Directionlets: anisotropic multi-directional representation with separable filtering [J]. IEEE Trans on Image Proc, 2006,15(7): 1916-1933.

孙文方,赵亦工,宋蓓蓓. 基于第二代Bandelets变换的静止图像压缩[J]. 西安交通大学学报, 2006, 40(8): 950-954.

Sun Wenfang,Zhao Yigong,Song Beibei.Still image compression based on the second generation Bandelets transform [J]. Journal of Xi'an Jiaotong University, 2006, 40(8): 950-954.

Taubman D. High performance scalable image compression with EBCOT [J]. IEEE Trans on Image Proc, 2000, 9(7): 1158-1170.

宋蓓蓓,许录平,孙文方. 一种基于小波的Contourlet变换的图像压缩算法[J]. 西安交通大学学报, 2007, 41(4): 479-483.

Song Beibei, Xu Luping, Sun Wenfang. Image compression algorithm using wavelet-based Contourlet transform [J]. Journal of Xi'an Jiaotong University, 2007,41(4): 479-483.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

基于区域特性的Contourlet域多聚焦图像融合算法

一种基于小波的Contourlet变换的图像压缩算法

采用试验设计方法的第三代CO2气体箔轴承箔片几何参数敏感性分析

多工况下离心压气机叶轮-机匣一体联合设计优化

隧道内燃料电池汽车氢气泄漏扩散特性及影响因素