Fast Algorithm for Nonsubsampled Contourlet Transform

Q2 Computer Science
Chun-Man YAN , Bao-Long GUO , Meng YI
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引用次数: 14

Abstract

The multiscale geometric analysis (MGA) has been recognized as an effective strategy for image processing. As one of the discrete tools of MGA, the nonsubsampled contourlet transform (NSCT) has been widely used for image denoising, image fusion, image enhancement, feature extraction and so on. However, the processing performance is limited due to its high redundancy, and leading to an intensive computational efficiency. Therefore, its fast algorithm is desired in practice. In this paper, we adopt an optimized directional filter bank (DFB) and embed it into the NSCT to significantly accelerate the computational speed while keeping slight loss of the reconstructed performance. Experimental results show that the reconstructed image quality can satisfy the human visual system. Moreover, the improved NSCT has a speed about several times than that of the traditional one. Experimental results on image denoising also validate the feasibility and efficiency of the proposed method.

非下采样Contourlet变换快速算法
多尺度几何分析(MGA)是一种有效的图像处理方法。非下采样contourlet变换(NSCT)作为MGA的离散化工具之一,在图像去噪、图像融合、图像增强、特征提取等方面得到了广泛的应用。然而,由于其高冗余性,限制了处理性能,导致了大量的计算效率。因此,在实际应用中需要快速的算法。在本文中,我们采用了一种优化的方向滤波器组(DFB)并将其嵌入到NSCT中,在保持重构性能轻微损失的同时显著加快了计算速度。实验结果表明,重构后的图像质量能够满足人眼视觉系统的要求。此外,改进的NSCT的速度是传统NSCT的几倍左右。图像去噪的实验结果也验证了该方法的可行性和有效性。
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来源期刊
自动化学报
自动化学报 Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
4.80
自引率
0.00%
发文量
6655
期刊介绍: ACTA AUTOMATICA SINICA is a joint publication of Chinese Association of Automation and the Institute of Automation, the Chinese Academy of Sciences. The objective is the high quality and rapid publication of the articles, with a strong focus on new trends, original theoretical and experimental research and developments, emerging technology, and industrial standards in automation.
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