中国科学院机构知识库网格系统: 检索

浏览/检索结果: 共4条，第1-4条

帮助

条数/页：排序方式：
	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：31/0 \| 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.
	A new research of sub-pixel level accuracy of TDICCD remote sensing image registration (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: 收藏 \| 浏览/下载：23/0 \| 提交时间：2013/03/25 In the field of remote sensing imaging TDICCD remote sensing images have a lot of their own characteristics such as high-resolution large amount of information less overlapping parts of pixels additional image blurring etc. Therefore there exist many difficulties especially in terms of high-accuracy registration of pairs of images. For that this paper presents two new pixel interpolation method for sub-pixel level registering images that allows for scaling translation and rotation. The proposed technique which is based on the maximization of the correlation coefficient function combines an efficient pixel-moving interpolation scheme with surface fitting which greatly reduces the overall computational cost. The accuracy of the algorithm is evaluated by calculating correlation coefficient of couples of points belonging to images transformed with preset factors and also comparing it to other sorts of methods. The experiment results show that the accuracy of registration reaches 0.01 pixels. 2010 IEEE.
	A real-time two-dimensional correlation speed measurement based on image (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: Yu L. 收藏 \| 浏览/下载：20/0 \| 提交时间：2013/03/25 In order to implement two-dimensional moving object's non-contact and real-time speed measurement in this paper wc proposed a new method which was based on the characteristic of FPGA and a real-time two-dimensional correlation speed measurement was proposed on image processing using high speed CMOS shown in figure 1. Experimental installation was shown in figure 2 a cardboard with images which was fixed in electric control movement device was moving to simulate moving object the CMOS image sensor gathered image signals of the cardboard and the image signals was output to FPGA after a serials pretreatment such as binaryzation etc. Logical operation insteaded mathematical operation on FPGA to implement two frames image's cross-correlation operations as the formula (10) in this paper and finally calculate the two-dimensional velocity. Through experiment result of table 1 we drawn an conclusion the accurarcy of the method in this paper was less than 1 pixel and the method can be used at a certain speed ranges of two-dimensional real-time speed measurement. 2010 IEEE.
	Target track system design based on circular projection (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China Song H.-J.; Zhu M.; Hu S.; Shen M.-L. 收藏 \| 浏览/下载：19/0 \| 提交时间：2013/03/25 Template matching is the process of searching the present and the location of a reference image or an object in a scene image. Template matching is a classical problem in a scene analysis: given a reference image of an object decide whether that object exists in a scene image under analysis and find its location if it does. The template matching process involves cross-correlating the template with the scene image and computing a measure of similarity between them to determine the displacement. The conventional matching method used the spatial cross-correlation process which is computationally expensive. Some algorithms are proposed for this speed problem such as pyramid algorithm but it still can't reach the real-time for bigger model image. Moreover the cross-correlation algorithm can't be effective when the object in the image is rotated. Therefore the conventional algorithms can't be used for practical purpose. In this paper an algorithm for a rotation invariant template matching method based on different value circular projection target tracking algorithm is proposed. This algorithm projects the model image as circular and gets the radius and the sum of the same radius pixel value. The sum of the same radius pixel value is invariable for the same image and the any rotated angle image. Therefore this algorithm has the rotation invariant property. In order to improve the matching speed and get the illumination invariance the different value method is combined with circular projection algorithm. This method computes the different value between model image radius pixel sum and the scene image radius pixel sum so that it gets the matching result. The pyramid algorithm also is been applied in order to improve the matching speed. The high speed hardware system also is been design in order to meet the real time requirement of target tracking system. The results show that this system has the good rotate invariance and real-time property.