机构

• 西安光学精密机械研究... [2]
• 长春光学精密机械与物... [1]
• 沈阳自动化研究所 [1]

采集方式

• OAI收割 [4]

内容类型

• 期刊论文 [2]
• 专著 [1]
• 会议论文 [1]

发表日期

• 2022 [1]
• 2015 [1]
• 2013 [1]
• 2010 [1]

学科主题

筛选

浏览/检索结果: 共4条，第1-4条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 All Weather Robot Vision 专著  OAI收割 Berlin:Springer Nature Singapore Pte Ltd., 2022 作者:  Tian JD(田建东)   |  收藏  |  浏览/下载：87/0  |  提交时间：2022/01/13 Robot vision  Reflectance recovery  Shadow detection  Shadow removal  Highlight removal  Intrinsic images  Rain removal  Snowflake removal  Fog removal  Underwater scattering  Light field   Accurate Normal and Reflectance Recovery Using Energy Optimization 期刊论文  OAI收割 ieee transactions on circuits and systems for video technology, 2015, 卷号: 25, 期号: 2, 页码: 212-224 作者:  Luo, Tao;  Shen, Jianbing;  Li, Xuelong 收藏  |  浏览/下载：29/0  |  提交时间：2015/07/14 Energy optimization  intrinsic images  normal recovery  reflectance   Intrinsic Image Decomposition Using Optimization and User Scribbles 期刊论文  OAI收割 ieee transactions on cybernetics, 2013, 卷号: 43, 期号: 2, 页码: 425-436 作者:  Shen, Jianbing;  Yang, Xiaoshan;  Li, Xuelong;  Jia, Yunde 收藏  |  浏览/下载：48/0  |  提交时间：2015/06/08 Energy optimization  illumination  intrinsic images  reflectance  user scribbles   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：34/0  |  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.