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Adaptive learning attention network for underwater image enhancement 期刊论文
IEEE Robotics and Automation Letters, 2022, 卷号: 7, 期号: 2, 页码: 5326-5333
作者:  Liu SB(刘世本);  Fan HJ(范慧杰);  Lin S(林森);  Wang Q(王强);  Ding ND(丁乃达)
收藏  |  浏览/下载：18/0  |  提交时间：2022/03/31
Outside Box and Contactless Palm Vein Recognition Based on a Wavelet Denoising ResNet 期刊论文
IEEE ACCESS, 2021, 卷号: 9, 页码: 82471-82484
作者:  Wu W(吴微);  Wang Q(王强);  Yu SQ(余思泉);  Luo Q(罗琼);  Lin S(林森)
收藏  |  浏览/下载：5/0  |  提交时间：2021/08/03
Detection of micro/nano-particle concentration using modulated light-emitting diode white light source 期刊论文
Sensors and Actuators, A: Physical, 2019, 卷号: 285, 页码: 89-97
作者:  Wang FF(王飞飞);  Yu HB(于海波);  Zhao WX(赵文秀);  Li WJ(李文荣);  Liu LQ(刘连庆)
收藏  |  浏览/下载：55/0  |  提交时间：2018/12/01
改进的单次散射相函数解析表达式 期刊论文
ACTA PHYSICA SINICA, 2017, 卷号: 66, 期号: 18, 页码: 1-12
作者:  崔生成;  史泽林;  程晨;  徐青山
收藏  |  浏览/下载：27/0  |  提交时间：2017/11/15
Pol-SAR Classification Based on Generalized Polar Decomposition of Mueller Matrix 期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2016, 卷号: 13, 期号: 4, 页码: 565-569
作者:  Wang, Hanning;  Zhou, Zhimin;  Turnbull, John;  Song, Qian;  Qi F(祁峰)
收藏  |  浏览/下载：21/0  |  提交时间：2016/04/30
尺度自适应暗通道先验去雾方法 期刊论文
红外与激光工程, 2016, 卷号: 45, 期号: 9, 页码: 286-297
作者:  宋颖超;  罗海波;  惠斌;  常铮
收藏  |  浏览/下载：24/0  |  提交时间：2016/11/06
SIMO detection schemes for underwater optical wireless communication under turbulence 期刊论文
PHOTONICS RESEARCH, 2015, 卷号: 3, 期号: 3, 页码: 48-53
作者:  Liu, Weihao;  Xu ZY(徐正元);  Yang, Liuqing
收藏  |  浏览/下载：31/0  |  提交时间：2015/08/24
A shape context based Hausdorff similarity measure in image matching 会议论文
5th International Symposium on Photoelectronic Detection and Imaging (ISPDI) - Infrared Imaging and Applications, Beijing, June 25-27, 2013
作者:  Ma TL(马天磊);  Liu YP(刘云鹏);  Shi ZL(史泽林);  Yin J(尹健)
收藏  |  浏览/下载：24/0  |  提交时间：2013/12/26
The traditional Hausdorff measure, which uses Euclidean distance metric (L2 norm) to define the distance between coordinates of any two points, has poor performance in the presence of the rotation and scale change although it is robust to the noise and occlusion. To address the problem, we define a novel similarity function including two parts in this paper. The first part is Hausdorff distance between shapes which is calculated by exploiting shape context that is rotation and scale invariant as the distance metric. The second part is the cost of matching between centroids. Unlike the traditional method, we use the centroid as reference point to obtain its shape context that embodies global information of the shape. Experiment results demonstrate that the function value between shapes is rotation and scale invariant and the matching accuracy of our algorithm is higher than that of previously proposed algorithm on the MEPG-7 database.  
A line mapping based automatic registration algorithm of infrared and visible images 会议论文
5th International Symposium on Photoelectronic Detection and Imaging (ISPDI) - Infrared Imaging and Applications, Beijing, June 25-27, 2013
作者:  Ai R(艾锐);  Shi ZL(史泽林);  Xu DJ(徐德江);  Zhang CS(张程硕)
收藏  |  浏览/下载：22/0  |  提交时间：2013/12/26
There exist complex gray mapping relationships among infrared and visible images because of the different imaging mechanisms. The difficulty of infrared and visible image registration is to find a reasonable similarity definition. In this paper, we develop a novel image similarity called implicit linesegment similarity(ILS) and a registration algorithm of infrared and visible images based on ILS. Essentially, the algorithm achieves image registration by aligning the corresponding line segment features in two images. First, we extract line segment features and record their coordinate positions in one of the images, and map these line segments into the second image based on the geometric transformation model. Then we iteratively maximize the degree of similarity between the line segment features and correspondence regions in the second image to obtain the model parameters. The advantage of doing this is no need directly measuring the gray similarity between the two images. We adopt a multi-resolution analysis method to calculate the model parameters from coarse to fine on Gaussian scale space. The geometric transformation parameters are finally obtained by the improved Powell algorithm. Comparative experiments demonstrate that the proposed algorithm can effectively achieve the automatic registration for infrared and visible images, and under considerable accuracy it makes a more significant improvement on computational efficiency and anti-noise ability than previously proposed algorithms.  
基于单目视觉的水下机械手自主作业方法研究 学位论文
硕士, 中国科学院沈阳自动化研究所: 中国科学院沈阳自动化研究所, 2012
作者:  霍良青
收藏  |  浏览/下载：85/0  |  提交时间：2012/07/27

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