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Chinese Academy of Sciences Institutional Repositories Grid
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机构
长春光学精密机械与物... [2]
地理科学与资源研究所 [1]
新疆生态与地理研究所 [1]
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OAI收割 [4]
内容类型
会议论文 [3]
期刊论文 [1]
发表日期
2024 [1]
2011 [1]
2008 [1]
2006 [1]
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Interaction between the Westerlies and Asian Monsoons in the Middle Latitudes of China: Review and Prospect
期刊论文
OAI收割
ATMOSPHERE, 2024, 卷号: 15, 期号: 3, 页码: 37
作者:
Li, Xiang-Jie
;
Zhu, Bing-Qi
  |  
收藏
  |  
浏览/下载:18/0
  |  
提交时间:2024/05/06
westerlies
Asian summer monsoon
circulation system
interaction
different time scale
mid-latitude region
Multi-focus image fusion algorithm based on adaptive PCNN and wavelet transform (EI CONFERENCE)
会议论文
OAI收割
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, May 24, 2011 - May 26, 2011, Beijing, China
Wu Z.-G.
;
Wang M.-J.
;
Han G.-L.
收藏
  |  
浏览/下载:78/0
  |  
提交时间:2013/03/25
Being an efficient method of information fusion
image fusion has been used in many fields such as machine vision
medical diagnosis
military applications and remote sensing.In this paper
Pulse Coupled Neural Network (PCNN) is introduced in this research field for its interesting properties in image processing
including segmentation
target recognition et al.
and a novel algorithm based on PCNN and Wavelet Transform for Multi-focus image fusion is proposed. First
the two original images are decomposed by wavelet transform. Then
based on the PCNN
a fusion rule in the Wavelet domain is given. This algorithm uses the wavelet coefficient in each frequency domain as the linking strength
so that its value can be chosen adaptively. Wavelet coefficients map to the range of image gray-scale. The output threshold function attenuates to minimum gray over time. Then all pixels of image get the ignition. So
the output of PCNN in each iteration time is ignition wavelet coefficients of threshold strength in different time. At this moment
the sequences of ignition of wavelet coefficients represent ignition timing of each neuron. The ignition timing of PCNN in each neuron is mapped to corresponding image gray-scale range
which is a picture of ignition timing mapping. Then it can judge the targets in the neuron are obvious features or not obvious. The fusion coefficients are decided by the compare-selection operator with the firing time gradient maps and the fusion image is reconstructed by wavelet inverse transform. Furthermore
by this algorithm
the threshold adjusting constant is estimated by appointed iteration number. Furthermore
In order to sufficient reflect order of the firing time
the threshold adjusting constant is estimated by appointed iteration number. So after the iteration achieved
each of the wavelet coefficient is activated. In order to verify the effectiveness of proposed rules
the experiments upon Multi-focus image are done. Moreover
comparative results of evaluating fusion quality are listed. The experimental results show that the method can effectively enhance the edge details and improve the spatial resolution of the image. 2011 SPIE.
Temporal and spatial characteristics of wet-dry climate variation in the northern slope of Tianshan Mountains, Xinjiang
会议论文
OAI收割
Proceedings of SPIE - The International Society for Optical Engineering, Guangzhou, China, 2008
Yu
;
Meiyan1
;
2
;
Chenxi
;
C.1
;
Bao
;
Anming1
收藏
  |  
浏览/下载:21/0
  |  
提交时间:2011/08/23
Geographic information systems - Landforms - Time series - Wavelet analysis - Wavelet transforms - Abrupt changes - Climate variation - Correlation analysis - Desert areas - Different time scale - Enso - Influence degrees - Mexican hat wavelets - Multi-time scale - Northern slope of tianshan mountains - Periodic oscillations - Rainfall datum - Regional characteristics - Research results - Temporal and spatial characteristics - Xinjiang
Intelligent MRTD testing for thermal imaging system using ANN (EI CONFERENCE)
会议论文
OAI收割
ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China
Sun J.
;
Ma D.
收藏
  |  
浏览/下载:27/0
  |  
提交时间:2013/03/25
The Minimum Resolvable Temperature Difference (MRTD) is the most widely accepted figure for describing the performance of a thermal imaging system. Many models have been proposed to predict it. The MRTD testing is a psychophysical task
for which biases are unavoidable. It requires laboratory conditions such as normal air condition and a constant temperature. It also needs expensive measuring equipments and takes a considerable period of time. Especially when measuring imagers of the same type
the test is time consuming. So an automated and intelligent measurement method should be discussed. This paper adopts the concept of automated MRTD testing using boundary contour system and fuzzy ARTMAP
but uses different methods. It describes an Automated MRTD Testing procedure basing on Back-Propagation Network. Firstly
we use frame grabber to capture the 4-bar target image data. Then according to image gray scale
we segment the image to get 4-bar place and extract feature vector representing the image characteristic and human detection ability. These feature sets
along with known target visibility
are used to train the ANN (Artificial Neural Networks). Actually it is a nonlinear classification (of input dimensions) of the image series using ANN. Our task is to justify if image is resolvable or uncertainty. Then the trained ANN will emulate observer performance in determining MRTD. This method can reduce the uncertainties between observers and long time dependent factors by standardization. This paper will introduce the feature extraction algorithm
demonstrate the feasibility of the whole process and give the accuracy of MRTD measurement.