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Research on Image Denoising New Method Based on Curvelet Transform

机译:基于Curvelet变换的图像去噪新方法研究。

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Wavelet transform only has spot singularity but curvelet transform has advantage of multi-scale singularity in each direction. After analyzing the method of image denoising by curvelet transform based on USFFT, the paper puts forward a new method VVCSC, which uses wrapping and cycle-spinning combined curvelet transform to improve existing algorithm. According to the simulated experiment, the results of the denoised pictures show that the improved algorithm has reduced the Pseudo-Gibbs phenomena, can reserve more detail information, texture of images and get higher seeing impression and PSNR value under the noise standard deviation.
机译:小波变换仅具有斑点奇异性,而曲波变换具有在每个方向上多尺度奇异性的优势。在分析了基于USFFT的Curvelet变换图像去噪方法之后,提出了一种新的VVCSC方法,该方法采用包裹和循环旋转结合Curvelet变换对现有算法进行了改进。根据仿真实验,去噪图像的结果表明,改进的算法减少了伪Gibbs现象,可以保留更多的细节信息,图像纹理,并且在噪声标准偏差下具有较高的观感和PSNR值。

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