首页> 外国专利> Nonlocal mean image denoising with detail preservation using blends driven by self-similarity

Nonlocal mean image denoising with detail preservation using blends driven by self-similarity

机译:使用由自相似驱动的混合来保留细节的非局部均值图像去噪

摘要

System, apparatus, method, and computer readable media for texture enhanced non-local means (NLM) image denoising. In embodiments, detail is preserved in filtered image data through a blending between the noisy input target pixel value and the NLM pixel value that is driven by self-similarity and further informed by an independent measure of local texture. In embodiments, the blending is driven by one or more blending weight or coefficient that is indicative of texture so that the level of detail preserved by the enhanced noise reduction filter scales with the amount of texture. Embodiments herein may thereby denoise regions of an image that lack significant texture (i.e. are smooth) more aggressively than more highly textured regions. In further embodiments, the blending coefficient is further determined based on similarity scores of candidate patches with the number of those scores considered being based on the texture score.
机译:用于纹理增强的非局部均值(NLM)图像降噪的系统,装置,方法和计算机可读介质。在实施例中,通过在噪声输入目标像素值和NLM像素值之间的混合来保留滤波后的图像数据中的细节,该混合由自相似性驱动并且进一步由局部纹理的独立度量来通知。在实施例中,通过指示纹理的一个或多个混合权重或系数来驱动混合,使得由增强的降噪滤波器保留的细节水平与纹理的数量成比例。因此,本文的实施例可以比具有更高纹理的区域更积极地对缺乏显着纹理(即,光滑)的图像区域进行降噪。在进一步的实施例中,基于候选补丁的相似性分数进一步确定混合系数,其中考虑的那些分数的数量基于纹理分数。

著录项

相似文献

  • 专利
  • 外文文献
  • 中文文献
获取专利

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