Improving Image Restoration with Soft-Rounding | |
Mei, Xing1,3![]() ![]() | |
2015 | |
会议日期 | 2015 |
会议地点 | Santiago, Chile |
英文摘要 |
Several important classes of images such as text, barcode and pattern images have the property that pixels can only take a distinct subset of values. This knowledge can benefit
the restoration of such images, but it has not been widely considered in current restoration methods. In this work, we describe an effective and efficient approach to incorporate
the knowledge of distinct pixel values of the pristine images into the general regularized least squares restoration frame-work. We introduce a new regularizer that attains zero at the designated pixel values and becomes a quadratic penalty function in the intervals between them. When incorporated into the regularized least squares restoration framework, this regularizer leads to a simple and efficient step that re-
sembles and extends the rounding operation, which we term as soft-rounding. We apply the soft-rounding enhanced solution to the restoration of binary text/barcode images and
pattern images with multiple distinct pixel values. Experimental results show that soft-rounding enhanced restoration methods achieve significant improvement in both visual
quality and quantitative measures (PSNR and SSIM). Furthermore, we show that this regularizer can also benefit the restoration of general natural images. |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/20005] ![]() |
专题 | 自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队 |
作者单位 | 1.Computer Science Department, University at Albany, SUNY 2.Computer Science Department, University of Chinese Academy of Sciences 3.NLPR, Institute of Automation, Chinese Academy of Sciences, Beijing, China |
推荐引用方式 GB/T 7714 | Mei, Xing,Qi, Honggang,Hu, Bao-Gang,et al. Improving Image Restoration with Soft-Rounding[C]. 见:. Santiago, Chile. 2015. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论