首页> 外文会议>IEEE International Conference on Information Science and Technology >Parallel domain decomposition based algorithm for large scale color image denoising
【24h】

Parallel domain decomposition based algorithm for large scale color image denoising

机译:基于并行域分解的大规模彩色图像去噪算法

获取原文

摘要

An effective method for recovering blocky and discontinuous images from noisy data is the Total variation (TV) method. In this paper, we introduce a parallel domain decomposition based Newton-Krylov-Schwarz (NKS) method to numerically solve the total variation minimization model for the color image restoration. We show numerically that the NKS method converges and scales well on parallel computers with over one thousand processors. Several numerical experiments and comparisons demonstrate that the proposed method is fast and robust, especially for large scale color images.
机译:从噪声数据中恢复块状和不连续图像的有效方法是总变化(TV)方法。在本文中,我们引入一种基于并行域分解的牛顿-克里洛夫-舒瓦兹(NKS)方法,以数值方式求解彩色图像恢复的总变化最小化模型。我们用数字显示,NKS方法在具有一千多个处理器的并行计算机上可以很好地收敛和扩展。若干数值实验和比较表明,该方法是快速且鲁棒的,特别是对于大规模彩色图像。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号