计算机科学 ›› 2012, Vol. 39 ›› Issue (3): 244-245.

• 图形图像 • 上一篇    下一篇

基于context模型的contourlet域图像去噪

刘镇弢,李涛,杜慧敏,韩俊刚   

  1. (西安电子科技大学微电子学院 西安 710071);(西安邮电学院电子工程学院 西安 710121)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Image Denosing Based on Context Model in Contourlet Domain

刘镇弢,李涛,杜慧敏,韩俊刚   

  • Online:2018-11-16 Published:2018-11-16

摘要: 在分析contourlet域系数分布特征的基础上提出了一种基于contex、模型的contourlet域图像去噪算法。算 法的关键点在于:基于contourlct变换系数的分布特性,确定合适的去噪门限;利用context模型建立图像contourlct 变换后的系数分类模型并根据分类使用不同的门限去噪。实验表明,本方法能较好地去除图像噪声,在提高去噪图像 PSNR值和改善主观视觉效果方面都表现出了良好的性能。

关键词: contourlct变换,图像去噪,context模型

Abstract: This paper presented an image denoising algorithm based on context model by analyzing distribution features of contourlets coefficients. I}he key of the proposed arithmetic is that through the analysis of C T coefficients distribution characteristics,we chose the appropriate denoising thresholding,adopted the context model to construct CI} coefficient's classification model,and according to different classification,image noise was removed by using different threshold. The experimental results show that the proposed algorithm can effectively remove the noise in images. The algorithm also demonstrates good performance in enhancing image PSNR and improves the image subjective visual impression.

Key words: Contourlet transform,Image denoising,Context model

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