Image denoising based on fast discrete curvelet transform

Journal of Computer Applications

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Image denoising based on fast discrete curvelet transform

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Received:2008-07-01 Revised:1900-01-01 Online:2008-12-01 Published:2008-12-01
Contact: Gao-Qiu Fang

基于快速离散曲波变换的图像去噪算法

方高球王正勇吴晓红

四川大学电子信息学院图像信息研究所四川大学电子信息学院图像信息研究所四川大学电子信息学院图像信息研究所

通讯作者: 方高球

Abstract

Abstract: Curvelet can reflect anisotropy of singular function and image edges; therefore it is better suitable for multiscale image denoising. According to the defects of the traditional thresholding methods, the diamond-shaped pieces thresholding algorithm combined with cycle spinning algorithm was proposed after analyzing the fast discrete curvelet transform based on wrapping algorithm, and the curvelet transform coefficients in different subbands were filtered with adaptive thresholds. The method can avoid image distortion due to the lack of translation invariance of curvelet transform, and can make use of correlation of curvelet coefficients better. Experimental results show that the proposed method yields denoised images with higher PSNR and better visual effects compared with the traditional wavelet denoising algorithm, the hard-threshold denoising method, the soft-threshold denoising method and the method between soft and hard thresholding based on curvelet transform.

Key words: Fast Discrete Curvelet Transform (FDCT), wrapping algorithm, cycle spinning algorithm, block threshold

摘要： Curvelet变换可以更好地表示曲线奇异函数的异向性及图像边缘，因此更适合于多尺度图像去噪。针对传统阈值法存在的不足，在分析wrapping方法的快速离散曲波变换基础上，提出结合Cycle Spinning循环平移方法的菱形块阈值规则去噪法，并自适应地对不同的Curvelet子块进行阈值化。该方法可以消除由于Curvelet变换缺乏平移不变性而产生的图像失真，并且更好地利用曲波系数的相关性。实验结果表明，该方法与传统的小波去噪、曲波硬阈值去噪、曲波软阈值去噪、曲波软硬阈值折中法去噪相比，使得去噪图像的峰值信噪比更高，视觉效果更好。

关键词: 快速离散曲波变换, wrapping算法, 循环平移算法, 块阈值

Gao-Qiu Fang Zheng-yong Wang Xiao-hong Wu. Image denoising based on fast discrete curvelet transform[J]. Journal of Computer Applications.

方高球王正勇吴晓红. 基于快速离散曲波变换的图像去噪算法[J]. 计算机应用.

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