中国科学院机构知识库网格系统: 检索

Identification of forest fire points under clear sky conditions with Himawari-8 satellite data 期刊论文 OAI收割
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2024, 卷号: 45, 期号: 1, 页码: 214-234
作者: Zhou, Wei; Tang, Bo-Hui; He, Zhi-Wei; Huang, Liang; Chen, Junyi

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收藏 | 浏览/下载：23/0 | 提交时间：2024/01/22

Forest fire Himawari-8 threshold-based algorithm random forest model dynamic identification

An improved hyperspectral classification algorithm based on back-propagation neural networks (EI CONFERENCE) 会议论文 OAI收割
2012 2nd International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2012, June 1, 2012 - June 3, 2012, Nanjing, China
作者: Yu P.; Yu P.

收藏 | 浏览/下载：34/0 | 提交时间：2013/03/25

In this paper a new method is proposed to improve the classification performance of hyperspectral images by combining the principal component analysis (PCA) genetic algorithm (GA) and artificial neural networks (ANNs). First some characteristics of the hyperspectral remotely sensed data such as high correlation high redundancy etc. are investigated. Based on the above analysis we propose to use the principal component analysis to capture the main information existing in the hyperspectral images and reduce its dimensionality consequently. Next we use neural networks to classify the reduced hyperspectral data. Since the back-propagation neural network we used is easy to suffer from the local minimum problem we adopt a genetic algorithm to optimize the BP network's weights and the threshold. Experimental results show that the classification accuracy is improved and the time of calculation is reduced as well. 2012 IEEE.

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.

The ship-borne infrared searching and tracking system based on the inertial platform (EI CONFERENCE) 会议论文 OAI收割
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China
作者: Li Y.; Zhang H.; Zhang H.; Li Y.; Li Y.

收藏 | 浏览/下载：38/0 | 提交时间：2013/03/25

As a result of the radar system got interferenced or in the state of half silent it can cause the guided precision drop badly In the modern electronic warfare therefore it can lead to the equipment depended on electronic guidance cannot strike the incoming goals exactly. It will need to rely on optoelectronic devices to make up for its shortcomings but when interference is in the process of radar leading especially the electro-optical equipment is influenced by the roll pitch and yaw rotation it can affect the target appear outside of the field of optoelectronic devices for a long time so the infrared optoelectronic equipment can not exert the superiority and also it cannot get across weapon-control system "reverse bring" missile against incoming goals. So the conventional ship-borne infrared system unable to track the target of incoming quickly the ability of optoelectronic rivalry declines heavily.Here we provide a brand new controlling algorithm for the semi-automatic searching and infrared tracking based on inertial navigation platform. Now it is applying well in our XX infrared optoelectronic searching and tracking system. The algorithm is mainly divided into two steps: The artificial mode turns into auto-searching when the deviation of guide exceeds the current scene under the course of leading for radar.When the threshold value of the image picked-up is satisfied by the contrast of the target in the searching scene the speed computed by using the CA model Least Square Method feeds back to the speed loop. And then combine the infrared information to accomplish the closed-loop control of the infrared optoelectronic system tracking. The algorithm is verified via experiment. Target capturing distance is 22.3 kilometers on the great lead deviation by using the algorithm. But without using the algorithm the capturing distance declines 12 kilometers. The algorithm advances the ability of infrared optoelectronic rivalry and declines the target capturing time by using semi-automatic searching and reliable capturing-tracking when the lead deviation of the radar is great. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

An adaptive edge detection method based on Canny operator (EI CONFERENCE) 会议论文 OAI收割
2011 International Conference on Civil Engineering and Building Materials, CEBM 2011, July 29, 2011 - July 31, 2011, Kunming, China
作者: Chen Y.

收藏 | 浏览/下载：41/0 | 提交时间：2013/03/25

This paper proposes an adaptive Canny operator edge detection algorithm. The proposed method can automatically set the threshold value according to the different image gray-scale gradient histogram adaptively and improve the performance in the detail edge detection and good localization. Experiments show that this method produces better edge detection results performance than the Otsu method. Besides our method Roberts operator Prewitt operator Sobel operator Log operator and Canny operator based on Otsu algorithm are also tested for comparisons. (2011) Trans Tech Publications Switzerland.

Automatic bridge extraction for optical images (EI CONFERENCE) 会议论文 OAI收割
6th International Conference on Image and Graphics, ICIG 2011, August 12, 2011 - August 15, 2011, Hefei, Anhui, China
Gu D.-Y.; Zhu C.-F.; Shen H.; Hu J.-Z.; Chang H.-X.

收藏 | 浏览/下载：32/0 | 提交时间：2013/03/25

This paper describes a novel hierarchy algorithm for extracting bridges over water in optical images. To reduce the omission of bridges by searching the edge we extract the river regions which the bridges are included in. Firstly we segment the optical image to get the coarse water bodies using iterative threshold eliminate the noise regions and add the missing regions based on k-means clustering with texture information and spatial coherence. Then the blanks are connected based on shape features and candidate bridge regions are segmented from river regions. Finally the bridges are verified by geometric information and the ubiety between bridges and river. The results show that this approach is efficient and effective for extracting bridges in satellite image from Google Earth and in aerial optical images acquired by unmanned aerial vehicle. 2011 IEEE.

The corner detector of teeth image based on the improved SUSAN algorithm (EI CONFERENCE) 会议论文 OAI收割
3rd International Conference on BioMedical Engineering and Informatics, BMEI 2010, October 16, 2010 - October 18, 2010, Yantai, China
作者: Yang L.; Yang L.; Wang X.; Wang X.; Wang X.

收藏 | 浏览/下载：18/0 | 提交时间：2013/03/25

In order to detect the corners of the teeth image secondly last we detected the corners of the image through the improved SUSAN corner detector algorithm. Through lots of experiments and comparing with other corner detector methods which were acquired by oral cavity endoscope we segmented the image by the threshold based on the gray value of the image this method can detect the corners of the teeth image effectively in this paper which can offer some available parameters for the 3D reconstruction of the teeth. 2010 IEEE. we used the improved SUSAN corner detector algorithm. In this method firstly we removed the noise of the image by the morphology open operation and median filtering

The research of corner detector of teeth image based on the curvature scale space corner algorithm (EI CONFERENCE) 会议论文 OAI收割
2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010, August 24, 2010 - August 26, 2010, Changchun, China
作者: Yang L.; Wang X.; Wang X.; Wang X.; Yang L.

收藏 | 浏览/下载：18/0 | 提交时间：2013/03/25

In order to detect the corners of the teeth image secondly thirdly last this method can detects the corners of the teeth image effectively which were acquired by oral cavity endoscope we segmented the image by the threshold based on the gray value of the image we detected the edge of the teeth image by the Canny edge detector we detected the corners by the adaptive threshold curvature scale corner detector. Through lots of experiments and we compare this method to other corner detector methods which offers some available parameters for the 3D reconstruction of the teeth. 2010 IEEE. in this paper we used the CSS algorithm. In this method firstly we removed the noise of the image by the morphology open operation and median filtering

Adaptive deformation estimation of moving target by weight image analysis (EI CONFERENCE) 会议论文 OAI收割
2010 2nd International Conference on Future Computer and Communication, ICFCC 2010, May 21, 2010 - May 24, 2010, Wuhan, China
Bai X.-G.; Dai M.

收藏 | 浏览/下载：27/0 | 提交时间：2013/03/25

An algorithm based on weight image analysis is proposed for adaptive deformation estimation of moving target in mean-shift tracking method. At the first we get the weight image from the target candidate region. Then we analyze the differences between the object and background. According to that the area estimation of the target can be converted into the image segmentation task. To realize the adaptive segmentation and estimation we define the threshold as the maximum variance between object and background. Combining the estimated area and covariance matrix we can estimate the width height and orientation of the object. The experimental results on three representative video sequences validate its robustness to the deformable estimation of the targets. 2010 IEEE.

Extracting sea-sky-line based on improved local complexity (EI CONFERENCE) 会议论文 OAI收割
2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010, August 24, 2010 - August 26, 2010, Changchun, China
作者: Zhang Y.-F.

收藏 | 浏览/下载：24/0 | 提交时间：2013/03/25

Sea-sky-line extraction under complicated sea-sky background is an important aspect of long-range target tracking research. An algorithm based on improved local complexity is proposed according to the feature that the sky and the sea usually show up at different gray levels in sea-sky background images. Median filter is applied first to remove peak noise and then the point set of sea-sky-line region which has the greatest change in image is obtained by calculating the local complexity of image and selecting a segmentation threshold. Finally Hough transform is used to extract the sea-sky-line. The experiment results indicate that this method can extract sea-sky-line under simple and complicated sea-sky backgrounds which is robust and can improve noise immunity of the algorithm. 2010 IEEE.