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Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
西安光学精密机械研究... [3]
长春光学精密机械与物... [1]
自动化研究所 [1]
采集方式
OAI收割 [5]
内容类型
会议论文 [4]
期刊论文 [1]
发表日期
2024 [1]
2019 [2]
2013 [1]
2008 [1]
学科主题
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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:2/0
  |  
提交时间:2024/09/13
autofocus
sharpness evaluation function
focusing window
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:41/0
  |  
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:18/0
  |  
提交时间:2020/03/04
auto-focus
sharpness evaluation function
threshold
gradient
SML
image processing
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:20/0
  |  
提交时间:2016/06/20
Depth Measurement
Depth Of Field
Image Fusion
Micro-image
Multi-focus
Sharpness Evaluation Function
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:20/0
  |  
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.