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	An Efficient Multiresolution Network for Vehicle Reidentification 期刊论文 OAI收割 IEEE INTERNET OF THINGS JOURNAL, 2022, 卷号: 9, 期号: 11, 页码: 9049-9059 作者: Shen, Fei; Zhu, Jianqing; Zhu, Xiaobin; Huang, Jingchang; Zeng, Huanqiang \| 收藏 \| 浏览/下载：46/0 \| 提交时间：2022/07/25 Image resolution Training Feature extraction Spatial resolution Proposals Internet of Things Deep learning Deep learning image representation multiresolution vehicle reidentification
	Directional multiscale edge detection using the contourlet transform (EI CONFERENCE) 会议论文 OAI收割 2010 IEEE International Conference on Advanced Computer Control, ICACC 2010, March 27, 2010 - March 29, 2010, 445 Hoes Lane - P.O.Box 1331, Piscataway, NJ 08855-1331, United States 作者: Jin L.-X.; Han S.-L.; Zhang R.-F. 收藏 \| 浏览/下载：43/0 \| 提交时间：2013/03/25 Wavelet multiresolution analysis allows us to detect edges at different scales also to obtain other important aspects of the extracted edges. However due to the usual two-dimensional tensor product wavelet transform is not optimal for representing images. The main problem in edge detection using wavelet transform is that it can only capture point-singularities and the extracted edges are not continuous. In order to solve that problem we propose a new image edge detection method based on the contourlet transform. The directional multiresolution representation Contourlet takes advantages of the intrinsic geometrical structure of images and is appropriate for the analysis of the image edges. Using the modulus maxima detection an image edge detection method based on contourlet transform is proposed. To suppress the image noise effect on edge detection the scale multiplication in contourlet domain is also proposed. Through real images experiments the proposed edge detection method's performance for the extracted edges is analyzed and compared with other two edge detection methods. The experiment result proves that the proposed edge detection method improves over wavelet-based techniques and Canny detector and also works well for noisy images. 2010 IEEE.
	Aerial image blurring caused by image motion and its restoration using wavelet transform (EI CONFERENCE) 会议论文 OAI收割 Electronic Imaging and Multimedia Technology IV, November 8, 2004 - November 11, 2004, Beijing, China 作者: Liu G. 收藏 \| 浏览/下载：39/0 \| 提交时间：2013/03/25 A wavelet-based approach of aerial blurred image restoration is proposed in this article. Image motion is inevitable in photographing for aerospace camera. Though some Image Motion Compensation(IMC) schemes are applied in aerial imaging system the ultimate image will be blurred in certain extent for the existence of IMC residual error while the forward image motion is the key element among all image motions which lead to image blurring. First the course of blurring caused by forward image motion is expressed using wavelet transform and a multiresolution sparse matrix representation of the degeneration model is obtained according to the wavelet transform. Subsequently a regularizing restoration algorithm is deduced from it and which can smoothly restraint the processed result efficiently. In the end the proposed approach is tested in MATLAB. The blurred image is restored using above-mentioned wavelet algorithm conventional contrary filter and Wiener filter algorithm separately. The conclusion that the wavelet-based restoration algorithm is superior to other two approaches is obtained by comparing the restored image's value of mean gradient. The calculating quantity of the wavelet-based blurred image restoration approach isn't large and it has good practicability in the field of image interpretation and aerial survey or drawing.
	Multiresolution locally expanded HONN for handwritten numeral recognition 期刊论文 OAI收割 PATTERN RECOGNITION LETTERS, 1997, 卷号: 18, 期号: 10, 页码: 1019-1025 作者: Liu, CL; Kim, JH; Dai, RW 收藏 \| 浏览/下载：14/0 \| 提交时间：2015/11/08 handwritten numeral recognition high order neural network local expansion multiresolution representation