机构

• 自动化研究所 [3]
• 西安光学精密机械研究... [3]
• 光电技术研究所 [2]
• 地质与地球物理研究所 [1]
• 长春光学精密机械与物... [1]
• 数学与系统科学研究院 [1]
• 更多

采集方式

• OAI收割 [11]

内容类型

• 期刊论文 [6]
• 会议论文 [4]
• 学位论文 [1]

发表日期

• 2024 [1]
• 2020 [1]
• 2019 [2]
• 2016 [2]
• 2015 [1]
• 2013 [1]
• 更多

学科主题

筛选

浏览/检索结果: 共11条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 Enhancement and suppression of nonsequential double ionization by spatially inhomogeneous fields 期刊论文  OAI收割 Optics Express, 2024, 卷号: 32, 期号: 11, 页码: 19825-19836 作者:  Luo, Xuan;  Jiao, Li Guang;  Liu, Aihua;  Liu, Xueshen   |  收藏  |  浏览/下载：3/0  |  提交时间：2024/09/13 autofocus  sharpness evaluation function  focusing window   Focal beam resolution analysis of wide-band, wide-azimuth and high-density land 3D seismic acquisition geometries 期刊论文  OAI收割 CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION, 2020, 卷号: 63, 期号: 10, 页码: 3868-3885 作者:  Chang ZiJuan;  Wei Wei;  Fu LiYun;  Qin Nan;  Su Jun   |  收藏  |  浏览/下载：34/0  |  提交时间：2020/12/07 Wide-band  wide-azimuth and high-density seismic acquisition  Focal beam resolution analysis  Imaging sharpness   Research of Image Sharpness Assessment Algorithm for Autofocus 会议论文  OAI收割 Xiamen, China, 2019-07-05 作者:  Her, Lilin;  Yang, Xiaojun   |  收藏  |  浏览/下载：44/0  |  提交时间：2020/05/28 sharpness evaluation function  autofocus  gradient operator  brenner algorithm   Auto-focus algorithm based on improved SML evaluation function 会议论文  OAI收割 Beijing, China, 2019-07-07 作者:  Ma, Xiaoyu;  Li, Qiaoling   |  收藏  |  浏览/下载：20/0  |  提交时间：2020/03/04 auto-focus  sharpness evaluation function  threshold  gradient  SML  image processing   A blur estimation and detection method for out-of-focus images 期刊论文  OAI收割 MULTIMEDIA TOOLS AND APPLICATIONS, 2016, 卷号: 75, 期号: 18, 页码: 10807-10822 作者:  Hong, Yuzhen;  Ren, Guoqiang;  Liu, Enhai;  Sun, Jian 收藏  |  浏览/下载：42/0  |  提交时间：2016/11/15 Sharpness  Blurriness  Blur detection  No-reference  Out-of-focus  PSF  Gradient profile   A no-reference image blurriness metric in the spatial domain 期刊论文  OAI收割 OPTIK, 2016, 卷号: 127, 期号: 14, 页码: 5568-5575 作者:  Hong, Yuzhen;  Ren, Guoqiang;  Liu, Enhai 收藏  |  浏览/下载：27/0  |  提交时间：2016/10/27 Sharpness metric  Blurriness metric  Image quality assessment  Spatial domain  JNB  No-reference   Tumor border sharpness correlates with HLA-G expression in low-grade gliomas 期刊论文  OAI收割 JOURNAL OF NEUROIMMUNOLOGY, 2015, 卷号: 282, 页码: 1-6 作者:  Wang, Yinyan;  Fan, Xing;  Li, Hongming;  Lin, Zhiguo;  Bao, Hongbo 收藏  |  浏览/下载：41/0  |  提交时间：2015/09/17 HLA-G  Low-grade glioma  Sharpness of the tumor border   Methods of Depth Measurement and Image Fusion Based on Multi-focus Micro-images 会议论文  OAI收割 Guiyang, 25-27 May 2013 作者:  Yin YingJie;  Wang, Xingang;  Xu, De;  Zhang, Zhengtao;  Bai, Mingran   |  收藏  |  浏览/下载：22/0  |  提交时间：2016/06/20 Depth Measurement  Depth Of Field  Image Fusion  Micro-image  Multi-focus  Sharpness Evaluation Function   视频画质增强算法及其硬件实现 学位论文  OAI收割 工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2011 作者:  汪彦刚 收藏  |  浏览/下载：174/0  |  提交时间：2015/09/02 视频增强  硬件体系结构  视频缩放  锐度增强  自动曝光控制  自动白平衡  Video enhancement  Hardware architecture  Video scaling  Sharpness enhancement  Auto exposure control  Auto white balance   Autofocusing technique based on image processing for remote-sensing camera (EI CONFERENCE) 会议论文  OAI收割 International Symposium on Photoelectronic Detection and Imaging 2007 - Image Processing, September 9, 2007 - September 12, 2007, Beijing, China 作者:  Wang X.;  Xu S.-Y.;  Wang X.;  Wang X. 收藏  |  浏览/下载：22/0  |  提交时间：2013/03/25 The key to the auto-focusing technique based on image processing is the selection of focus measure reflecting image definition. Usually the measures derived are on the premise of the images acquired with the same scene. As for the remote-sensing camera working in linear CCD push-broom imaging mode  the premise doesn't exist because the scenes shot are different at any moment  which brings about difficulties to the selection of the focus measure. To evaluate the image definition  the focus measure based on blur estimation for rough adjustment is proposed to estimate the focused position by only two different lens positions  which greatly saves the auto-focusing time. Another evaluation function based on edge sharpness is developed to find best imaging position in the narrow range. Simulations show that the combination of the two measures has the advantages of rapid reaction and high accuracy.