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Research of Image Denoising Method Based on Part Adaptive Total Variation and Median Filter

机译:基于零件自适应总变化和中值滤波的图像去噪方法研究

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According to the advantage of median filter and total variation algorithm, a new median filter adaptive total variation model based on part gradient of image pixels is established in the paper. At first, the new model uses the gradient information of every pixel of the image to find out the isolated noise point and then uses the median filter to remove it. Second, the adaptive total variation algorithm to deal with the new noise image is adopted. The new method proposed in the paper not only surmounts the disadvantage of generating artificial edge but also has the advantages of denoising and edges preservation of TV model. The experiments show that the PSNR of the improved method increases almost 1.0dB compared with the adaptive model at the same noisy level.
机译:根据中值滤波和总变化算法的优点,建立了基于图像像素局部梯度的中值滤波自适应总变化模型。首先,新模型使用图像每个像素的梯度信息找出孤立的噪声点,然后使用中值滤波器将其删除。其次,采用自适应总变化算法处理新的噪声图像。本文提出的新方法不仅克服了产生人工边缘的缺点,而且具有电视模型去噪和边缘保留的优点。实验表明,在相同噪声水平下,与自适应模型相比,改进方法的PSNR提高了近1.0dB。

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