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长春光学精密机械与物... [8]
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期刊论文 [4]
会议论文 [3]
学位论文 [1]
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2022 [1]
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专题:长春光学精密机械与物理研究所
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A SpatialSpectral Combination Method for Hyperspectral Band Selection
期刊论文
Remote Sensing, 2022, 卷号: 14, 页码: 13
作者:
X. Han
;
Z. Jiang
;
Y. Liu
;
J. Zhao
;
Q. Sun and Y. Li
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浏览/下载:0/0
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提交时间:2023/06/14
A temperature and emissivity separation algorithm based on maximum entropy estimation of alpha spectrum's scaling and translation
期刊论文
Acta Physica Sinica, 2015, 卷号: 64, 期号: 17, 页码: 11
作者:
Liu, J. C.
;
H. W. Li
;
J. L. Wang
;
X. Y. Liu and X. X. Ma
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  |  
浏览/下载:15/0
  |  
提交时间:2016/07/15
Inversion of emissivity spectrum and temperature in the TIR waveband based on the Maximum Entropy
期刊论文
Infrared Physics & Technology, 2015, 卷号: 72, 页码: 179-190
作者:
Liu, J. C.
;
H. W. Li
;
J. L. Wang
;
H. Z. Li
;
L. M. Yin and Z. D. Zhang
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  |  
浏览/下载:18/0
  |  
提交时间:2016/07/15
航空图像超分辨率重构技术研究
学位论文
博士: 中国科学院大学, 2014
杨文波
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浏览/下载:59/0
  |  
提交时间:2014/08/21
Selection Method for Kernel Function in Nonparametric Extrapolation Based on Multicriteria Decision-Making Technology
期刊论文
Mathematical Problems in Engineering, 2013
Wang J. X.
;
Liu Y.
;
Zeng X. H.
;
Zhou Z. P.
;
Wang N. X.
;
Shen W. H.
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  |  
浏览/下载:13/0
  |  
提交时间:2014/05/14
Algorithm of image enhancement based on order morphology transformation (EI CONFERENCE)
会议论文
2009 International Forum on Information Technology and Applications, IFITA 2009, May 15, 2009 - May 17, 2009, Chengdu, China
Yan H.
;
Zhao X.
;
Liu Y.
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浏览/下载:12/0
  |  
提交时间:2013/03/25
A method based Tsallis entropy and order morphology transform for gray image enhancement is proposed in this article. The order morphology transform method improves the evaluation guide of transform
and chose the percentile value and structure B value by the Maximum Tsallis entropy of the area where the coefficient q is 0.8
enhances the gray image. Experiments show that the method enhances the image contrast and suppressing noise and extracting edge. The histogram and gray value show that the image contrast is improved. 2009 IEEE.
An improved two-dimensional entropy method for star trail tracing in deep sky (EI CONFERENCE)
会议论文
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
Yao Z.-J.
;
Wang Y.-J.
;
Han Q.-L.
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浏览/下载:15/0
  |  
提交时间:2013/03/25
The trace of star trail is an important component of deep sky detection. The stars are low contrast targets
and their self-rotation will make their brightness change in cycle. Above all
the trail trace is vulnerable to the block and disturbance of other stars. Traditional one-dimensional maximum entropy thresholding algorithm is vulnerable to the noise
and the calculation of two-dimensional entropy methods is too large and takes too much time. This paper proposes an improved two-dimensional entropy threshold algorithm. We use recursion iteration method to eliminate the redundancy calculation
and reduce the size of two-dimensional histogram based on the deep sky stars characteristic
such as low contrast
fuzziness and the centralized histogram. We also combine our algorithm with the space trail trace model to forecast the star trace. Experiments results show
when the star are blocked or they turn dark
the method still can well extrapolate the star trace. Our method improves the capability of trailing the ebb and small star
and increases the precision of tracing. It is also robust to the noise
so there is a good application foreground for the method.
An edge extracting method of fuzzy thresholding value (EI CONFERENCE)
会议论文
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
Gu R.
;
Zhu M.
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  |  
浏览/下载:13/0
  |  
提交时间:2013/03/25
This paper discusses image's object edge extracting of threshold value. First
this paper introduces fundamental principle of gray image object edge extracting
after discussing the influence of object edge image's gray scale distributing characteristic and choice of threshold value to character extracting and target identification
we bring forward a sort of method
which using object edge fuzzy taxonomy and maximum fuzzy entropy theory to auto choose threshold value in the case that membership function is given
then we have a test of threshold value segmentation to edge gray image in different contrast
the result indicates this method has preferable scene adaptive faculty.
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