The effectness of image denoising between sparse decomposition and wavelet soft thresholding denosing are compared. According to the vision effect,image denosing results based on sparse decomposition is better than that of wavelet soft thresholding.
比较了稀疏分解图像去噪与小波软阈值去噪效果,就视觉效果来看,基于稀疏分解的图像去噪效果要好于小波软阈值的去噪效果。
参考来源 - 基于匹配跟踪和自适应字典的图像去噪算法研究·2,447,543篇论文数据，部分数据来源于NoteExpress
Soft thresholding method has been a standard procedure in signal de-noising.
软阈值消噪是信号消噪中的标准算法。
Theoretical analysis shows that the proposed method can effectively reduce the lower bound of denoising error of the wavelet denoising method based on soft thresholding.
理论分析表明，该方法能有效地降低软阈值小波降噪法的误差下界。
Soft Thresholding Wavelet-based Radial Basis Function Neural network (STWRBFN) method was developed to perform simultaneous quantitative analysis of multicomponent mixtures.
建立了一种小波软阈值径向基函数神经网络(STWRBFN)方法，同时定量分析了多组分混合物。
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