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浏览/检索结果: 共6条，第1-6条 帮助 限定条件 专题：长春光学精密机械与物理研究所    第一署名单位    第一作者单位    通讯作者单位     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 A new research of sub-pixel level accuracy of TDICCD remote sensing image registration (EI CONFERENCE) 会议论文 2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010, August 24, 2010 - August 26, 2010, Changchun, China Lu J.; He B.; Cong Y. 收藏  |  浏览/下载：19/0  |  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.   Scene matching based on directional keylines and polar transform (EI CONFERENCE) 会议论文 2010 IEEE 10th International Conference on Signal Processing, ICSP2010, October 24, 2010 - October 28, 2010, Beijing, China Zhang Y.; Qu H.; Wang Y. 收藏  |  浏览/下载：19/0  |  提交时间：2013/03/25 Scene matching under complex background is a priority and difficulty in the field of computer vision  it has the characteristics of rotation and scaling invariance  commonly used in matching real-time collected images and photos for navigation. Scene matching techniques are faced with complex natural scenes  anti-light and anti-slight-distortion  the image distortion exist  applicable for complex scene matching. The project has a new idea: combining the keylines with the vectors description based on polar image translation  such as light  and utilize the rotation-scale-invariance vectors to describe the extracted keylines  change of gray levels  this method includes three steps: keylines extraction  perspective  description and matching. Preliminary experiments show that this keylines-based scene matching algorithm is applicable for image matching under complex background. 2010 IEEE.  scaling and other differences  which cause matching difficult. This paper aims to find a scene matching algorithm   Image registration based on log-polar transform and SIFT features (EI CONFERENCE) 会议论文 2010 International Conference on Computational and Information Sciences, ICCIS2010, December 17, 2010 - December 19, 2010, Chengdu, Sichuan, China Ding N.; Liu Y.; Jin Y.; Zhu M. 收藏  |  浏览/下载：14/0  |  提交时间：2013/03/25 This paper describes a novel image registration method that combines log-polar transform and SIFT to recover similarity transformations (rotation/ scale/ translation).We extracts SIFT feature points in the two images firstly. Then  we use threshold Euclidean distance to coarsely match the feature points. After that  the log-polar transform is applied to compute the rotation and scale parameters. And we can obtain the translation parameter by the location relationship of the feature points. 2010 IEEE.   Mean shift tracking combining SIFT (EI CONFERENCE) 会议论文 2008 9th International Conference on Signal Processing, ICSP 2008, October 26, 2008 - October 29, 2008, Beijing, China Chen A.-H.; Zhu M.; Wang Y.-H.; Xue C. 收藏  |  浏览/下载：54/0  |  提交时间：2013/03/25 A novel visual tracking algorithm to cope with occlusion and scale variation is proposed. This method combines mean shift and SIFT algorithm to track object. SIFT algorithm is invariant to rotation  translation and scale variation. But it is a timeconsuming algorithm. The wasting time is related to image size. So the proposed algorithm first adopts mean shift to initially locate object position  then SIFT operator is used to detect features in object area and model area  lastly  the proposed method matches features in these two areas and calculates the relationship between them using affine transform. According to affine transform parameters  the state of object can be adjusted in time. In order to reduce process time  an improved feature matching algorithm is proposed in this paper. Experiments show that the proposed algorithm deals with occlusion successfully and can adjust object size in time. 2008 IEEE.   A novel starting-point-independent wavelet coefficient shape matching (EI CONFERENCE) 会议论文 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China Hu S.; Zhu M.; Wu C.; Song H.-J. 收藏  |  浏览/下载：12/0  |  提交时间：2013/03/25 In many computer vision tasks  in order to improve the accuracy and robustness to the noise  wavelet analysis is preferred for the natural multi-resolution property. However  the wavelet representation suffers from the dependency of the starting point of the sampled contour. For overcoming the problem that the wavelet representation depends on the starting point of the sampled contour  the Zernike moments are introduced  and a novel Starting-Point-lndependent wavelet coefficient shape matching algorithm is presented. The proposed matching algorithm firstly gains the object contours  and give the translation and scale invariant object shape representation. The object shape representation is converted to the dyadic wavelet representation by the wavelet transform. And then calculate the Zernike moments of wavelet representation in different scales. With respect to property of rotation invariant of Zernike moments  consider the Zernike moments as the feature vector to calculate the dissimilarity between the object and template image  which overcoming the problem of dependency of starting point. The experimental results have proved the proposed algorithm to be efficient  precise  and robust.   PSO based gabor wavelet feature extraction method (EI CONFERENCE) 会议论文 2004 International Conference on Information Acquisition, ICIA 2004, June 21, 2004 - June 25, 2004, Hefei, China Sun H.; Pan Y.; Zhang Y. 收藏  |  浏览/下载：13/0  |  提交时间：2013/03/25 In this paper  the time of feature extraction is faster. By test in low contrast image  2D continues Gabor wavelets are adopted to realize feature extraction. By optimize Gabor wavelet's parameters of translation  the feasibility and effectiveness of the algorithm are demonstrated by VC++ simulation platform in experiments. 2004 IEEE.  orientation  and scale to make it approximates a local image contour region. The method of Sobel edge detection is used to get the initial position and orientation value of optimization in order to improve the convergence speed. In the wavelet characteristic space  we adopt PSO (particle swarm optimization) Algorithm to identify points on the security border of the system. Comparing to the LM algorithm  it can ensure reliable convergence the target  which can improve convergent speed