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USFFTCurvelet

于 2011-05-27 发布 文件大小:750KB
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  提出了一种结合USFFT Curvelet 变换的各向异性扩散图像去噪模型。它有机结合了Curvelet 变换和各向 异性扩散(P-M扩散)两者的优点。通过P-范数方法选择合适的梯度阈值K,P-M扩散过程通过处理经过Curvelet 变换得到的图像的不同尺度的Curvelet 系数矩阵,实现了建立在对图像多尺度分析的基础上的新P-M扩散模型。 实验表明,新模型的处理结果能有效避免传统P-M 扩散出现的阶梯效应,同时更好地保留图像的纹理和细节。 关键词:图像去噪算法;各向异性扩散;Curvelet 变换;P-M 扩散(Abstract: An image de-noising model by integrating anisotropic diffusion with USFFT Curvelet transform was proposed, which combined the strongpoint of Curvelet transform with anisotropic diffusion (P-M diffusion). By choosing appropriate gradient threshold K through p-norms and carrying out the P-M diffusion process depend on the different scale matrixes of Curvelet coefficient of the image from Curvelet transform iterations, as a result, the improved model made it possible to carry out the new P-M diffusion de-noising process based on multi-scale analysis of the image. The experiment results have demonstrated that the model can avert the stair-casing effect in the traditional P-M diffusion effectively and keep the textures and details of images better.)

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