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加权变分去噪模型的分裂Bregman算法 被引量:2

Split Bregman algorithm of the weighted variation model for image denoising
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摘要 针对求解加权变分去噪模型时大量迭代导致计算速度缓慢的问题,为提高运算速度,在加权变分去噪模型中引入分裂Bregman算法。实验表明,与梯度下降法相比,该算法迭代次数少、处理过程快,极大地缩短了运算时间,并且保持了较好的去噪效果。 Aiming at the complex computaion of the weighted variation model for denoising which is caused by a large number of iterations in denoising process,the Split Bregman method is applied in the weighted variation model for increasing the computation speed.Numerical results demonstrate that the proposed algorithm is faster than the gradient descent algorithm and can keep denoising effect better.
出处 《桂林电子科技大学学报》 2011年第4期322-325,共4页 Journal of Guilin University of Electronic Technology
基金 国家自然科学基金(10871217)
关键词 图像处理 图像去噪 加权变分模型 分裂Bregman算法 image processing image denoising the weighted variation model split Bregman algorithm
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