中国科学院机构知识库网格系统: 检索

Multi-focus image fusion dataset and algorithm test in real environment 期刊论文 OAI收割
FRONTIERS IN NEUROROBOTICS, 2022, 卷号: 16, 页码: 8
作者: Liu, Shuaiqi; Peng, Weijian; Jiang, Wenjing; Yang, Yang; Zhao, Jie

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收藏 | 浏览/下载：35/0 | 提交时间：2022/12/27

image fusion multi-focus image fusion dataset image preprocessing multi-focus image fusion algorithm test real environment

Research on image preprocessing techniques needed for long-distance camera scanning fourier ptychographic imaging 会议论文 OAI收割
Xiamen, PEOPLES R CHINA, 2020-08-25
作者: Wang, Jing; Zhao, Hui; Yang, Mingyang; Li, Zhixin; Xiang, Meng

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收藏 | 浏览/下载：25/0 | 提交时间：2021/06/04

fourier ptychographic imaging camera scanning image preprocessing image quality assessment

Astronomical image restoration through atmosphere turbulence by lucky imaging (EI CONFERENCE) 会议论文 OAI收割
3rd International Conference on Digital Image Processing, ICDIP 2011, April 15, 2011 - April 17, 2011, Chengdu, China
作者: Zhao J.; Wang J.; Zhang S.

收藏 | 浏览/下载：27/0 | 提交时间：2013/03/25

In this paper we develop a lucky imaging system to restore astronomical images through atmosphere turbulence. Our system takes very short exposures on the order of the atmospheric coherence time. The rapidly changing turbulence leads to a very variable point spread function (PSF) and the variability of the PSF leads to some frames having better quality than the rest. Only the best frames are selected aligned and co-added to give a final image with much improved angular resolution. Our system mainly consists of five parts: preprocessing frame selection image registration image reconstruction and image enhancement. Our lucky imaging system has been successfully applied to restore the astronomical images taken by a 1.23m telescope. We have got clear images of moon surface and Jupiter and our system can be demonstrated to greatly improve the imaging resolution through atmospheric turbulence. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

Research on infrared dim-point target detection and tracking under sea-sky-line complex background (EI CONFERENCE) 会议论文 OAI收割
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China
作者: Dong Y.-X.; Zhang H.-B.; Li Y.; Li Y.; Li Y.

收藏 | 浏览/下载：111/0 | 提交时间：2013/03/25

Target detection and tracking technology in infrared image is an important part of modern military defense system. Infrared dim-point targets detection and recognition under complex background is a difficulty and important strategic value and challenging research topic. The main objects that carrier-borne infrared vigilance system detected are sea-skimming aircrafts and missiles. Due to the characteristics of wide field of view of vigilance system the target is usually under the sea clutter. Detection and recognition of the target will be taken great difficulties.There are some traditional point target detection algorithms such as adaptive background prediction detecting method. When background has dispersion-decreasing structure the traditional target detection algorithms would be more useful. But when the background has large gray gradient such as sea-sky-line sea waves etc.The bigger false-alarm rate will be taken in these local area.It could not obtain satisfactory results. Because dim-point target itself does not have obvious geometry or texture feature in our opinion from the perspective of mathematics the detection of dim-point targets in image is about singular function analysis.And from the perspective image processing analysis the judgment of isolated singularity in the image is key problem. The foregoing points for dim-point targets detection its essence is a separation of target and background of different singularity characteristics.The image from infrared sensor usually accompanied by different kinds of noise. These external noises could be caused by the complicated background or from the sensor itself. The noise might affect target detection and tracking. Therefore the purpose of the image preprocessing is to reduce the effects from noise also to raise the SNR of image and to increase the contrast of target and background. According to the low sea-skimming infrared flying small target characteristics the median filter is used to eliminate noise improve signal-to-noise ratio then the multi-point multi-storey vertical Sobel algorithm will be used to detect the sea-sky-line so that we can segment sea and sky in the image. Finally using centroid tracking method to capture and trace target. This method has been successfully used to trace target under the sea-sky complex background. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

虹膜图像预处理与特征分析 学位论文 OAI收割
工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2010
作者: 何召锋

收藏 | 浏览/下载：226/0 | 提交时间：2015/09/02

生物特征识别虹膜识别虹膜图像预处理特征选择和分类器设计 Adaboost学习算法 Biometrics iris recognition iris image preprocessing feature selection and classifier design Adaboost learning

Design of multispectral remote sensing image compression system (EI CONFERENCE) 会议论文 OAI收割
2010 International Conference on Computer Application and System Modeling, ICCASM 2010, October 22, 2010 - October 24, 2010, Shanxi, Taiyuan, China
作者: Xu S.-Y.

收藏 | 浏览/下载：19/0 | 提交时间：2013/03/25

In order to get the higher compression quality of multispectral remote sensing image which taken the JPEG2000 as the standard used FPGA and special compression chip ADV212 to realize the remote sensing image compression system is proposed. The system used the specialty compression chip ADV212 which is newly relaesed by Analog Device company. It used to develop fast high-quality compression for the large amount of remote sensing image data. The system realized the image data's input the compression stream's output the image preprocessing as well as to control the ADV212 chip's working pattern through FPGA. The experiment result shows that this system which has such characteristics as low power consumption. low cost and easy adjustmen and has a good compressing effect. Meet the requirement of the multispectral remote sensing image's high compression ratio. 2010 IEEE.

Joint transform correlator based on joint image feature extraction using swarm intelligence method (EI CONFERENCE) 会议论文 OAI收割
2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009, August 9, 2009 - August 12, 2009, Changchun, China
作者: Wang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Y.

收藏 | 浏览/下载：15/0 | 提交时间：2013/03/25

An image feature extraction method based on Swarm Intelligence is used in the preprocessing of joint image in joint transform correlator. The Swarm Intelligence based image processing method is superior to the conventional image processing method in its robust flexible fault tolerant scalable and highly parallelizable characteristic. The output results from the classical JTC without image preprocessing and the JTC with Sobel operator based joint image feature extraction are compared with that of the JTC when using the Swarm Intelligence to extract the feature of joint image. Experiment results show the performance improvement of JTC using the feature extraction method based on Swarm Intelligence. 2009 IEEE.

Input plane preprocessing of joint transform correlator based on Swarm Intelligence (EI CONFERENCE) 会议论文 OAI收割
2009 2nd International Congress on Image and Signal Processing, CISP'09, October 17, 2009 - October 19, 2009, Tianjin, China
Yong W.; Ming Z.

收藏 | 浏览/下载：23/0 | 提交时间：2013/03/25

Input plane image preprocessing can improve the performance of Joint Transform Correlator(JTC). Swarm Intelligence based image processing method is consistent with the parallel characteristic of optical signal processing method. In this paper A Swarm Intelligence based input plane preprocessing method is proposed. Some other methods are also used to perform the task such as grayscale transform Sobel operator and mathematical morphology. The experimental results show that the performance of the proposed Swarm Intelligence preprocessing based JTC is better than that of the JTC based on other preprocessing methods. 2009 IEEE.

Research of Face Detection System Applied for Detecting Faces with Complex Background and Illumination 会议论文 OAI收割
5th international conference on fuzzy systems and knowledge discovery, jinan, peoples r china, oct 18-20, 2008
Dai L; Li WJ; Chen X; Jin XX; Qu YF

收藏 | 浏览/下载：58/0 | 提交时间：2010/03/09

image preprocessing

Color transfer and Retinex theory based illumination invariance 会议论文 OAI收割
International Conference on Information Computing and Automation, Hefei, China, December 20-22, 2007
作者: Sun J(孙静); Tang YD(唐延东)

收藏 | 浏览/下载：20/0 | 提交时间：2012/06/06

illumination invariance color transfer Retinex image preprocessing