...
首页> 外文期刊>International Journal of Engineering Research and Applications >Image Restoration and Denoising By Using Nonlocally Centralized Sparse Representation and Histogram Clipping
【24h】

Image Restoration and Denoising By Using Nonlocally Centralized Sparse Representation and Histogram Clipping

机译:

获取原文
           

摘要

Due to the degradation of observed image the noisy, blurred, Distorted image can be occurred .for restoring image information we propose the sparse representations by conventional modelsmay not be accurate enough for a faithful reconstruction of the original image. To improve the performance of sparse representation-based image restoration,In this method the sparse coding noise is added for image restoration, due to this image restoration the sparse coefficients of original image can be detected. The so-called nonlocally centralized sparse representation (NCSR) model is as simple as the standard sparse representation model,for denoising the image here we use the Histogram clipping method by using histogram based sparse representation effectively reduce the noise.and also implement the TMR filter for Quality image.various types of image restoration problems, including denoising, deblurring and super-resolution, validate the generality and state-of-the-art performance of the proposed algorithm.

著录项

相似文献

  • 外文文献
  • 中文文献
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