CHEN Jun.Application of medical image denoising with total variation of curvelet transform[J].Journal of Yanbian University,2021,47(04):361-364.
全变差曲波变换在医学影像图像去噪中的应用
- Title:
- Application of medical image denoising with total variation of curvelet transform
- 文章编号:
- 1004-4353(2021)04-0361-04
- Keywords:
- medical image; denoising; curvelet transform; total variation; image composition
- 分类号:
- TP391.4
- 文献标志码:
- A
- 摘要:
- 针对曲波变换算法在医学影像图像去噪中会产生截断伪影和边缘模糊等问题,提出了一种全变差曲波变换算法.该算法首先对含噪医学影像图像分别进行曲波阈值和全变差去噪,然后将得到的去噪结果进行曲波逆变换并生成最终图像.仿真实验结果表明,该算法不仅可有效地降低噪声,还可较好地保持医学影像图像边缘和细节信息,其效果明显优于曲波变换算法和全变差算法.因此,该算法对医学影像图像的噪声滤除具有良好的应用价值.
- Abstract:
- To solve the problems of the truncated pseudimage and edge blur caused by curvelet transform algorithm in medical image noise removal, a curvelet transform of total variation algorithm is proposed. The method firstly performs noise removal for the noise - containing medical image through the curvelet threshold and total variation respectively, then transforms the obtained denoising results to generate the final image. Simulation results show that this algorithm can not only effectively reduce noise, but also maintain the edge and detail information of medical image, which is significantly better than the curvelet transform algorithm and total variation algorithm. Therefore, the proposed algorithm has a good application value for the noise filtering of the medical image.
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备注/Memo
收稿日期: 2021-10-08
基金项目: 甘肃省科技计划资助项目(20JR10RA327)
作者简介: 陈军(1969—),男,博士,教授,研究方向为医学信号处理.