Image Restoration and Decomposition Based on Curvelet Domain

JIANG Ling-ling; FENG Xiang-chu; YIN Hai-qing

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Image Restoration and Decomposition Based on Curvelet Domain

更新时间：2025-07-16

- Image Restoration and Decomposition Based on Curvelet Domain
- Acta Electronica Sinica Vol. 36, Issue 9, Pages: 1790-1794(2008)
- 作者机构：
  
  1. 西安电子科技大学理学院,陕西,西安,710071
  2. 中国石油大学数学与计算科学学院,山东,东营,257061
  3. 西安电子科技大学理学院陕西西安,710071
  4. 中国石油大学数学与计算科学学院山东东营,257061
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911
- Published Online：25 September 2008，
  
  Published：2008
- 稿件说明：
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JIANG Ling-ling, FENG Xiang-chu, YIN Hai-qing. Image Restoration and Decomposition Based on Curvelet Domain[J]. Acta Electronica Sinica, 2008, 36(9): 1790-1794.
DOI：

JIANG Ling-ling, FENG Xiang-chu, YIN Hai-qing. Image Restoration and Decomposition Based on Curvelet Domain[J]. Acta Electronica Sinica, 2008, 36(9): 1790-1794. DOI：

摘要

第二代Curvelet变换是继小波变换之后

能更适合图像处理特点的一种多尺度变换

它能同时获得对图像平滑区域和边缘部分的稀疏表示

且具有很强的方向性.针对它的优点

提出了一种基于第二代Curvelet阈值的图像复原和分解的新模型.本文首先在负指数Hilbert-Sobolev空间推广了Daubechies-Teschke模型

接着对推广的模型在Curvelet域上进行处理.实验结果表明该模型不仅可以很好地分解图像、去除噪声

而且可以去模糊

使图像有较好的视觉效果.

Abstract

The Curvelet is more suitable for image processing than the wavelet and able to represent smooth and edge parts of image with sparsity.Based on the advantages of curvelet

we present a novel method for image restoration and decomposition via curvelet shrinkage.The new model can be seen as generalizations of Daubechies-Teschke’s model.By writing the problem in a curvelet framework

we obtain elegant curvelet shrinkage schemes.Various numerical results on denoising

deblurring and decomposition of images are presented and they show that the model is valid.

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