| 图像去噪的改进自适应全变差正则化模型 |
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| 引用本文： | 郭晓龙,吴传生,刘文,李云廷. 图像去噪的改进自适应全变差正则化模型[J]. 武汉理工大学学报(信息与管理工程版), 2011, 33(2): 200-202. DOI: 10.3963/j.issn.1007-144X.2011.02.008 |
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| 作者姓名： | 郭晓龙 吴传生 刘文 李云廷 |
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| 作者单位： | 武汉理工大学理学院,湖北,武汉,430070 |
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| 基金项目： | 国家大学生创新性实验计划基金资助项目，武汉理工大学自主创新研究基金资助项目 |
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| 摘 要： | 针对经典全变差正则化模型在去噪时图像边缘易模糊的不足,在全变差正则化模型与调和去噪模型的基础上构建了一种改进的自适应全变差正则化模型,并利用旋转不变性更好的梯度模值确定其自适应参数,降低该自适应正则化模型对噪声的敏感性,以兼顾图像的平滑去噪与边缘保留。数值实验结果表明,与MARQUINA的改进全变差正则化模型相比,自适应全变差正则化模型的复原图像在视觉效果和峰值信噪比上都有显著提高。
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| 关 键 词： | 全变差正则化 图像去噪 自适应 峰值信噪比 |
A Modified Adaptive Total Variation Regularization Model for Image Denoising |
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| GUO Xiaolong,WU Chuansheng,LIU Wen,LI Yunting. A Modified Adaptive Total Variation Regularization Model for Image Denoising[J]. Journal of Wuhan University of Technology(Information & Management Engineering), 2011, 33(2): 200-202. DOI: 10.3963/j.issn.1007-144X.2011.02.008 |
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| Authors: | GUO Xiaolong WU Chuansheng LIU Wen LI Yunting |
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| Affiliation: | GUO Xiaolong:Postgraduate,School of Science,WUT,Wuhan 430070,China.,WU Chuansheng,LIU Wen,LI Yunting |
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| Abstract: | The total variation (TV) regularization model is considered to be one of the best denoising models.But the image edges are easy to be blurred while using the TV model to denoise.A modified adaptive total variation (ATV) regularization model based on the TV model and harmonic model was proposed in this paper.The gradient norm with steady rotational invariance was introduced to choose the adaptive parameter adaptively,which was used to reduce the sensitivity of ATV model to noises.The numerical results show t... |
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| Keywords: | total variation regularization image denoising adaptive peak signal to noise ratio |
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