图像去噪理论基础图像视频去噪的最终目的是改善给定的图像，解决实际图像由于噪声干扰而导致图像质量下降的问题。通过去噪技术可以有效地提高图像质量，增大信噪比，更好的体现原来图像所携带的信息，作为一种重要的预处理手段，人们对图像去噪算法进行了广泛的研究。在现有的去噪算法中，有的去噪算法在低维信号图像处理中取得较好的效果，却不适用于高维信号图像处理；或者去噪效果较好，却丢失部分图像边缘信息，或者致力于研究检测图像边缘信息，保留图像细节。-Image denoising theory based image video denoising s ultimate aim is to improve a given image, to solve practical image due to noise interference of the decline of the image quality. By denoising technology can effectively improve the image quality, increase the signal-to-noise ratio, better reflect the information carried by the original image, as a kind of important means of pretreatment, the image denoising algorithm is extensively studied. In the existing denoising algorithms, some of the denoising algorithm in low visa obtained better effect in image processing, but it does not apply to higher dimensional signal image processing　Or better denoising effect, but loss of part of the image edge information, or devoted to detect image edge information, keep image details.