An algorithm of adaptive total variation image denoising

作者：Niu He Ming^*; Du Qian; Zhang Jian Xun

来源：Pattem Recognition and Aitificial Intelligence, 2011, 24(6): 780-803.

• Blurred image
• Edge information
• Evolution equations
• Global variables
• Image denoising algorithm
• Image noise
• Local information
• Noise variance
• Noise variations
• Noisy image
• Partial differential
• Total variation

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.

• 出版日期2011
• 单位南开大学