格子玻尔兹曼模型的各向异性扩散图像去噪

Zhiqiang Wang, Zhuangzhi Yan, Y. Qian, George Chen
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引用次数: 5

摘要

为了克服传统数值方法实现各向异性扩散模型图像去噪的低效率,本文提出了一种新的各向异性扩散晶格玻尔兹曼模型。在该模型中,扩散速率与图像本身相适应,并对每个扩散方向独立设置。质量累积是通过粒子分布函数的加权求和来计算的。该方法在迭代步长较大的情况下具有稳定性,从而大大减少了迭代步长。实验结果表明,与其他方法相比,我们的方法在生成的图像和计算效率方面表现更好。此外,我们的方法易于并行实现。
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Lattice Boltzmann model of anisotropic diffusion for image denoising
To overcome the inefficiency of the traditional numerical methods that implement the anisotropic diffusion model for image denoising, a novel lattice Boltzmann model of anisotropic diffusion is presented in this paper. In the model, the diffusion rate is adapted to the image itself and independently set for each direction of diffusion. The mass accumulation is calculated through a weighted summation of the particle distribution functions. Our method is stable with large iteration steps thus reducing the iteration steps greatly. The experiment results showed that compared to others, our approach performs better in terms of the resulting images as well as computing efficiency. In addition, our approach is easy for parallel implementation.
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