| 一种基于自适应阈值的图像去噪新方法 |
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| 引用本文： | 尚晓清 王军锋 宋国乡. 一种基于自适应阈值的图像去噪新方法[J]. 计算机科学, 2003, 30(9): 70-71 |
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| 作者姓名： | 尚晓清 王军锋 宋国乡 |
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| 作者单位： | 西安电子科技大学理学院数学系,西安,710071 |
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| 基金项目： | 陕西省自然科学基金(2000SL02)资助项目. |
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| 摘 要： | Selecting threshold is the most important in threshold-based nonlinear filtering by wavelet transform. In this paper, a novel adaptive threshold is proposed by minimizing a Bayesian risk(It is adaptive to subband because it depends on data-driven estimates of the parameters). Combining this thresholding method with Wiener fitting can re-sult a new denoising method. Expermental results show that the proposed method indeed remove noise significantly and retaining most image edges. The results compare favorably with the reported results in the recent denoising liter-ature.
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| 关 键 词： | 自适应阈值 图像去噪方法 马尔科夫模型 小波系数 图像处理 |
Adaptive Wavelet Thresholding for Image Denoising |
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| SHANG Xiao-Qing WANG Jun-Feng SONG Guo-Xiang. Adaptive Wavelet Thresholding for Image Denoising[J]. Computer Science, 2003, 30(9): 70-71 |
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| Authors: | SHANG Xiao-Qing WANG Jun-Feng SONG Guo-Xiang |
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| Abstract: | Selecting threshold is the most important in threshold.based nonlinear filtering by wavelet transform. In this paper, a novel adaptive threshold is proposed by minimizing a Bayesian risk (It is adaptive to subband because it depends on data-driven estimates of the parameters). Combining this thresholding method with Wiener filting can result a new denoising method. Expermental results show that the proposed method indeed remove noise significantly and retaining most image edges. The results compare favorably with the reported results in the recent denoising literature. |
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| Keywords: | Image processing Shrinkage denoising Wavelet transform |
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