...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Image Processing, IEEE Transactions on >Framelet Algorithms for De-Blurring Images Corrupted by Impulse Plus Gaussian Noise
【24h】

Framelet Algorithms for De-Blurring Images Corrupted by Impulse Plus Gaussian Noise

机译：用于脉冲加高斯噪声破坏的图像去模糊的小框架算法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper studies a problem of image restoration that observed images are contaminated by Gaussian and impulse noise. Existing methods for this problem in the literature are based on minimizing an objective functional having the $ell^{1}$ fidelity term and the Mumford–Shah regularizer. We present an algorithm on this problem by minimizing a new objective functional. The proposed functional has a content-dependent fidelity term which assimilates the strength of fidelity terms measured by the $ell^{1}$ and $ell^{2}$ norms. The regularizer in the functional is formed by the $ell^{1}$ norm of tight framelet coefficients of the underlying image. The selected tight framelet filters are able to extract geometric features of images. We then propose an iterative framelet-based approximation/sparsity deblurring algorithm (IFASDA) for the proposed functional. Parameters in IFASDA are adaptively varying at each iteration and are determined automatically. In this sense, IFASDA is a parameter-free algorithm. This advantage makes the algorithm more attractive and practical. The effectiveness of IFASDA is experimentally illustrated on problems of image deblurring with Gaussian and impulse noise. Improvements in both PSNR and visual quality of IFASDA over a typical existing method are demonstrated. In addition, Fast_IFASDA, an accelerated algorithm of IFASDA, is also developed.
机译：本文研究了图像恢复问题，即观察到的图像受到高斯和脉冲噪声的污染。文献中针对此问题的现有方法基于最小化具有 $ ell ^ {1} $ 保真度项的目标函数以及Mumford-Shah正则化器。通过最小化新的目标函数，我们提出了针对此问题的算法。提议的功能具有依赖于内容的保真度术语，该保真度术语吸收了 $ ell ^ {1} $ 和 $ ell ^ {2} $ 规范。函数中的正则化器由基础图像的紧框架系数的 $ ell ^ {1} $ 范数形成。选定的紧密小框架滤镜能够提取图像的几何特征。然后，我们针对所提出的功能提出了一种基于迭代小框架的近似/稀疏去模糊算法（IFASDA）。 IFASDA中的参数在每次迭代时都会自适应地变化，并自动确定。从这个意义上讲，IFASDA是一种无参数算法。这个优点使算法更具吸引力和实用性。 IFASDA的有效性通过高斯和脉冲噪声对图像去模糊的问题进行了实验证明。展示了IFASDA的PSNR和视觉质量在典型现有方法上的改进。另外，还开发了IFASDA的加速算法Fast_IFASDA。

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