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| An Algorithm of Adaptive Total Variation Image Denoising |
| NIU He-Ming, DU Qian, ZHANG Jian-Xun |
| Institute of Robotics and Automatic Information System, Nankai University, Tianjin 300071 |
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Abstract Aiming at the algorithm of traditional total variation image denoising which needs to know the noise variance and staircase of the object, an algorithm of adaptive total variation image denoising is proposed. The approximation item of traditional algorithm is modified by replacing the original noisy image with a blurred image, thus it is not necessary to know the noise variation of the image, and the impact of image noise in fidelity item is also reduced. Lagrange multiplier is no longer a global variable, as well as its numerical size is determined by image local information. Simultaneously, Lagrange multiplier is weighted by approximate edge information. So the evolution of the image can be expressed in a unified evolution equation. The experimental results and data analysis show that the proposed algorithm is superior to the traditional total variation image denoising algorithm.
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Received: 15 February 2011
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2011, Vol. 24 
