标题:EFFECTIVE DOCUMENT IMAGE DEBLURRING VIA GRADIENT HISTOGRAM PRESERVATION
作者:Zhang, Mingli; Desrosiers, Christian; Zhang, Caiming; Cheriet, Mohamed
作者机构:[Zhang, Mingli; Desrosiers, Christian; Cheriet, Mohamed] Ecole Technol Super, Montreal, PQ H3C 1K3, Canada.; [Zhang, Caiming] Shandong Univ, Sch Com 更多
会议名称:IEEE International Conference on Image Processing (ICIP)
会议日期:SEP 27-30, 2015
来源:2015 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)
出版年:2015
卷:2015-December
页码:779-783
DOI:10.1109/ICIP.2015.7350905
关键词:Document image deblurring; Gradient Histogram Preservation; Variable; Splitting
摘要:Traditional deblurring algorithms are often focused on natural-scaled images, which are not adapted for document texts and images without having some negative impacts on the accuracy of the OCR and the visual quality. In this paper, we propose a gradient histogram preservation method. An effective optimization method was developed and achieves satisfying results for kernel estimation. By combining the gradient histogram preservation prior with conventional image deblurring methods, it significantly improves the simulations and experimental results on document images and a high SSIM is achieved with the proposed method.
收录类别:CPCI-S;EI;SCOPUS
WOS核心被引频次:2
Scopus被引频次:5
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84956619358&doi=10.1109%2fICIP.2015.7350905&partnerID=40&md5=6679f84c7d322e5dcd9ebb12b40d6e40
TOP