一种基于压缩感知全变差算法的图像去噪方法

Method for Image Denoising Based on Compressed Sensing Total Variation Algorithm

压缩感知技术突破了奈奎斯特准则的局限性,在图像处理方面有着广泛的应用。提出一种改进的基于压缩感知的图像去噪方法。该方法中,对混有噪声的图像首先进行稀疏变换,然后对变换后的部分系数采用测量矩阵进行测量,最后通过全变差(TV)重建算法进行图像重建。仿真结果证实全变差重建算法在图像去噪中优于其他压缩感知重建算法,可以有效地去除图像中混有的噪声,实现图像的良好去噪。

Compressed sensing technology breaks the limitation of Nyquist sampling criterion and has widespread use in image processing. A approach for image denoising based on compressed sensing is presented in this paper. In this method, an unknown noisy image of interest is transformed and sensed through a limited number linear functional in random projection, then original image is reconstructed using the observation vector and the existed recovery algorithms. Simulation results inform this total variance reconstruction algorithm is more efficient than other compressed sensing reconstruction algorithms for image denoising.