一种基于全变分技术和Lp伪范数的椒盐噪声去除方法

针对传统各向同性全变分（Isotropy total variation，ITV）去噪算法容易导致图像边缘模糊、不易保持图像细节信息等问题，提出一种基于L _p 伪范数和各向同性全变分的图像去噪方法。该方法将L _p 伪范数代替ITV模型中的L ₁范数，利用交替方向乘子算法（Alternating direction method of multipliers, ADMM）将能量泛函拆解成若干个子问题，并将差分算子视为卷积算子；然后引入卷积定理和快速傅里叶变换(Fast Fourier transform, FFT)提高算法运算效率；最后通过Matlab进行仿真实验，运用图像质量的客观和主观评价方法进行评价分析。结果表明，本文方法能够较好地保留图像的边缘特性，有效提升去噪效果。

Method of Removing Salt and Pepper Noise Based on Total Variation Technique and L p Pseudo-Norm

In the framework of the traditional isotropic total variation (ITV) denoising algorithm, the edge of the image is easily blurred, and it is difficult to maintain the image detail information. Thus, we mainly study the image denoising problem by using L _p pseudo-norm and ITV. The L _p pseudo-norm takes place the L ₁ norm in traditional ITV energy function. Then the energy function is broken into several sub-problems by using alternating direction method of multipliers (ADMM). We treat the differential operator as a convolution operator, then introduce the convolution theorem and the fast Fourier transform (FFT) to further improve the efficiency of the proposed method. Finally, through Matlab, the simulation experiment employs the objective and subjective evaluation methods of image quality for evaluation and analysis. Simulation results show that the proposed method is capable of preserving the edge characteristics of the image and improving the denoising effect efficiently.