鲍金. 模糊视频图像的小波阈值去噪算法研究[J]. 微电子学与计算机, 2018, 35(8): 113-116.
引用本文: 鲍金. 模糊视频图像的小波阈值去噪算法研究[J]. 微电子学与计算机, 2018, 35(8): 113-116.
BAO Jin. Research on Wavelet Threshold Denoising Algorithm for Fuzzy Video Images[J]. Microelectronics & Computer, 2018, 35(8): 113-116.
Citation: BAO Jin. Research on Wavelet Threshold Denoising Algorithm for Fuzzy Video Images[J]. Microelectronics & Computer, 2018, 35(8): 113-116.

模糊视频图像的小波阈值去噪算法研究

Research on Wavelet Threshold Denoising Algorithm for Fuzzy Video Images

  • 摘要: 由于传统的模糊视频图像的小波阈值去噪算法, 无法大幅度提高分辨率图像.提出模糊视频图像小波阈值去噪算法优化.对模糊视频图像进行融合处理, 该融合过程首先利用重心化的空间相似变换模型组建多光谱影像粗配准模型, 检测高分辨率影像的边缘点和非边缘点.组建模糊视频图像去噪模型, 提取影像重要边缘信息和纹理信息, 得到影像的独立分量特征, 完成模糊视频图像的小波阈值去噪算法的优化.实验结果表明, 所提算法对模糊视频图像去噪效果较好, 可以完成任意角度视频影像与点云的高精度去噪.

     

    Abstract: Because of the wavelet threshold de-noising algorithm of the traditional fuzzy video image, the resolution image can not be greatly improved. A wavelet threshold de-noising algorithm for fuzzy video image is proposed. The fusion of fuzzy video images is carried out. First, we use the spatial similarity transformation model of gravity center to form the coarse registration model of multispectral images, and detect the edge points and non edge points of high resolution images. A fuzzy video image denoising model is established, and the important edge information and texture information of the image are extracted to get the independent component features of the image, and the optimization of the wavelet threshold denoising algorithm of the fuzzy video image is completed. The experimental results show that the proposed algorithm has good denoising effect on the fuzzy video image, and can complete the high precision denoising of the video image and the point cloud at any angle.

     

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