计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (21): 174-177.

• 图形、图像、模式识别 • 上一篇    下一篇

Contourlet收缩和全变差相结合的图像去噪

齐志强1,曲怀敬2   

  1. 1.济南职业学院 计算机系,济南 250100
    2.山东建筑大学 信息与电气工程学院,济南 250101
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2011-07-21 发布日期:2011-07-21

Image denoising combining Contourlet shrinkage with total variation

QI Zhiqiang1,QU Huaijing2   

  1. 1.Department of Computer Science,Jinan Vocational College,Jinan 250100,China
    2.School of Information & Electric Engineering,Shandong Jianzhu University,Jinan 250101,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-07-21 Published:2011-07-21

摘要: 充分保持细节的图像去噪在图像处理领域具有重要的意义。一种新的将Contourlet收缩和全变差相结合的混合去噪算法被提出。利用空域自适应的全变差,对含噪图像与Contourlet硬阈值收缩图像的差值图像进行滤波。再和收缩图像相叠加,从而得到最终的去噪图像。实验结果表明,和现有的典型去噪方法相比较,所提出的算法在有效去除噪声和Gibbs伪影的同时,更好地保持了边缘和纹理等重要的细节信息。

关键词: Contourlet变换, 全变差, 细节保持, 去噪

Abstract: Image denoising with details sufficiently preserved has important significance in image processing field.A novel hybrid denoising algorithm is proposed,which combines the contourlet shrinkage method with the total variation approach.Using the spatially adaptive total variation,the difference image between the noisy image and the contourlet hard-threshold shrinkage image is filtered.The filtered difference image is added back to the shrinkage image to get the final denoised image.Experimental results show that,compared with existing typical denoising methods,the proposed algorithm can effectively remove the noise and Gibbs-like artifacts,and has superior performance in preserving the important detail information,such as edges and textures.

Key words: Contourlet transform, total variation, detail-preserving, denoising