徐立军, 杨秋翔, 雷海卫. 一种基于压缩感知的改进全变分图像去噪方法[J]. 微电子学与计算机, 2016, 33(6): 100-103.
引用本文: 徐立军, 杨秋翔, 雷海卫. 一种基于压缩感知的改进全变分图像去噪方法[J]. 微电子学与计算机, 2016, 33(6): 100-103.
XU Li-jun, YANG Qiu-xiang, LEI Hai-wei. An Improved Total Variation for Image Denoising Based on Compressed Sensing[J]. Microelectronics & Computer, 2016, 33(6): 100-103.
Citation: XU Li-jun, YANG Qiu-xiang, LEI Hai-wei. An Improved Total Variation for Image Denoising Based on Compressed Sensing[J]. Microelectronics & Computer, 2016, 33(6): 100-103.

一种基于压缩感知的改进全变分图像去噪方法

An Improved Total Variation for Image Denoising Based on Compressed Sensing

  • 摘要: 提出了一种基于压缩感知理论的改进的全变分算法来实现图像的去噪.该方法中, 首先对含噪图像进行稀疏表示, 然后采用高斯随机矩阵进行测量, 最后通过全变分(TV)算法重建图像.仿真实验表明, 与传统的去噪方法相比, 该方法能有效地去除图像中的噪声, 获得更高的峰值信噪比, 并且图像的边缘细节得到了很好的保护, 验证了算法的有效性.

     

    Abstract: This paper uses the improved total variation for image denosing based on compressed sending. In this method, nosiy image is transformed and sensed through a Gaussian random projection, then original images is reconstructed using the total variation reconstruction algorithms. Simulation experiments show that comparing to the original method, the method can eliminate the noise in image effectively and get a higher peak signal to noise ratio, and the image detail can be well protected and proves the effeciency of the algorithm.

     

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