发布求助
文献互助 智能选刊 最新文献

2016 IEEE International Conference on Signal and Image Processing (ICSIP)最新文献

筛选
英文 中文
Research on compressed sensing equalization algorithms 压缩感知均衡算法研究
2016 IEEE International Conference on Signal and Image Processing (ICSIP) Pub Date : 2016-08-01 DOI: 10.1109/SIPROCESS.2016.7888248
J. Ren, T. Tang
{"title":"Research on compressed sensing equalization algorithms","authors":"J. Ren, T. Tang","doi":"10.1109/SIPROCESS.2016.7888248","DOIUrl":"https://doi.org/10.1109/SIPROCESS.2016.7888248","url":null,"abstract":"Digital image is generally used in various fields in real life. Massive photos of rapid acquisition become an important content of the signal processing. Compressed sensing (CS) theory undersampling technology provides a new image transmission storage as well as new thought. Algorithm which obtains the image may appear halation, fuzzy, and other problems aroused by many sorts of problems. In order to meet the demand of more advanced image evaluation standard, homogenization treatment is required. This paper is aimed to improve the image quality combined with the compressed perception theory and is mainly based on the equalization algorithm.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"156 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128104730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Time-frequency characteristics of PSWF with Wigner-Ville Distributions 具有Wigner-Ville分布的PSWF时频特性
2016 IEEE International Conference on Signal and Image Processing (ICSIP) Pub Date : 2016-08-01 DOI: 10.1109/SIPROCESS.2016.7888326
Lu Faping, Wang Hongxing, Liu Xiao, Liu Chuanhui, Kang Jiafang, Miao Xingji
{"title":"Time-frequency characteristics of PSWF with Wigner-Ville Distributions","authors":"Lu Faping, Wang Hongxing, Liu Xiao, Liu Chuanhui, Kang Jiafang, Miao Xingji","doi":"10.1109/SIPROCESS.2016.7888326","DOIUrl":"https://doi.org/10.1109/SIPROCESS.2016.7888326","url":null,"abstract":"The existing study and application of Prolate Spheroidal Wave Function (PSWF) primarily around the characteristics of PSWF in a single energy domain, the characteristics of PSWF in two-dimensional time-frequency energy domain have not been mining and using, from the perspective of signal time-frequency distribution, Wigner-Ville Distribution with higher time-frequency resolution was introduced to study the time-frequency characteristics of PSWF. The simulation results shows that the PSWF with different parameters with different time-frequency distribution characteristics; at the same time, through the comparison those different of time-frequency distribution, a deeper understanding of the characteristics of PSWF was known, which could further improve the foundation PSWF properties, look for efficient information loading and testing way, and significantly improve the application value of PSWF.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133307504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Graph Laplacian and dictionary learning, Lagrangian method for image denoising 图拉普拉斯和字典学习，拉格朗日图像去噪方法
2016 IEEE International Conference on Signal and Image Processing (ICSIP) Pub Date : 2016-08-01 DOI: 10.1109/SIPROCESS.2016.7888259
Yibin Yu, Pengfei Guo, Yinxing Chen, Peng Chen, K. Guo
{"title":"Graph Laplacian and dictionary learning, Lagrangian method for image denoising","authors":"Yibin Yu, Pengfei Guo, Yinxing Chen, Peng Chen, K. Guo","doi":"10.1109/SIPROCESS.2016.7888259","DOIUrl":"https://doi.org/10.1109/SIPROCESS.2016.7888259","url":null,"abstract":"Removing the noise while keeping the image features like edges, textures is a challenging problem in image denoising. Because it is an under-determined problem, defining appropriate image priors to regularize the problem plays an important role. Recently a popular one among proposed image priors is the graph Laplacian regularizer, which can exploit the local geometry structure of the image. Introducing a graph Laplacian matrix term and a dictionary learning term, in this paper we propose a new model to restore the original image. The objective consists of a data fidelity term, a graph Laplacian regularizer term and a sparse representation term. To solve this non-convex model, we propose an alternating minimization method via Lagrangian optimization. In addition, we choose the eigenvectors of the normalized graph Laplacian matrix as the initial dictionary for the sparse coding. Experimental results demonstrate that the proposed model outperforms BF and NLM, in terms of both objective measurements and perceptual quality.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132337912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Detection of heartbeats based on the Bayesian framework 基于贝叶斯框架的心跳检测
2016 IEEE International Conference on Signal and Image Processing (ICSIP) Pub Date : 2016-08-01 DOI: 10.1109/SIPROCESS.2016.7888335
Wen-Long Chin, Jong-Hun Yu, Cheng-Lung Tseng
{"title":"Detection of heartbeats based on the Bayesian framework","authors":"Wen-Long Chin, Jong-Hun Yu, Cheng-Lung Tseng","doi":"10.1109/SIPROCESS.2016.7888335","DOIUrl":"https://doi.org/10.1109/SIPROCESS.2016.7888335","url":null,"abstract":"The detection of heartbeat is an important and challenging issue for health care. This work proposes to estimate the QRS complex parameters based on the maximum-likelihood (ML) principle. To this goal, a new signal model and its Bayesian framework are studied. Detectors or estimators based on the Bayesian framework are considered to be optimal in the statistical signal processing point of view. To reduce the complexity of original method, its iterative counterpart is investigated by using the decomposition method. Detailed information of QRS complexes, including the starting point, duration, and period, can be derived by the proposed method for further medical diagnosis. Simulations using the benchmark MIT-BIH Arrhythmia database verify the advantages of the proposed approaches compared to traditional ones.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117061752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A modified coherent hough method for pulse-train signal integration 脉冲序列信号积分的改进相干霍夫方法
2016 IEEE International Conference on Signal and Image Processing (ICSIP) Pub Date : 2016-08-01 DOI: 10.1109/SIPROCESS.2016.7888311
Shuai Ding, Hui Wang, Defeng Chen, Tuo Fu
{"title":"A modified coherent hough method for pulse-train signal integration","authors":"Shuai Ding, Hui Wang, Defeng Chen, Tuo Fu","doi":"10.1109/SIPROCESS.2016.7888311","DOIUrl":"https://doi.org/10.1109/SIPROCESS.2016.7888311","url":null,"abstract":"A coherent Hough method is proposed here to integrate the pulse-train signal. Based on a narrowband echo model, the suggested method implements the coherent integration by compensating the modulated phase terms from pulse to pulse before applying Hough transform. The improved method outperforms standard Hough transform, particularly in a very low SNR environment. The algorithm's performance is analyzed and its validity is further verified by simulation experiments.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124443858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A modified M-SIFT algorithm for matching images with different viewing angle 一种改进的M-SIFT算法用于不同视角图像的匹配
2016 IEEE International Conference on Signal and Image Processing (ICSIP) Pub Date : 2016-08-01 DOI: 10.1109/SIPROCESS.2016.7888261
Wenchao Hu, W. Zhou, J. Guan
{"title":"A modified M-SIFT algorithm for matching images with different viewing angle","authors":"Wenchao Hu, W. Zhou, J. Guan","doi":"10.1109/SIPROCESS.2016.7888261","DOIUrl":"https://doi.org/10.1109/SIPROCESS.2016.7888261","url":null,"abstract":"In this paper, we propose an affine invariant image matching algorithm, which is based on the well-known SIFT algorithm. Firstly, we use MSER algorithm to detect affine invariant feature regions. Then covariance matrix of an image patch is used to transform anisotropic patches into isotropic patches by rotating and squeezing. Finally, the affine invariant key points on isotropic patches are detected by SIFT algorithm. Experiments show that M-SIFT works well with large affine angle changes and scale changes compared with SIFT algorithm.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122582729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Novel imaging method based on cross-correlation function for suppressing the interference of noise 基于互相关函数抑制噪声干扰的成像新方法
2016 IEEE International Conference on Signal and Image Processing (ICSIP) Pub Date : 2016-08-01 DOI: 10.1109/SIPROCESS.2016.7888262
Guangmin Zhang, Yue Song
{"title":"Novel imaging method based on cross-correlation function for suppressing the interference of noise","authors":"Guangmin Zhang, Yue Song","doi":"10.1109/SIPROCESS.2016.7888262","DOIUrl":"https://doi.org/10.1109/SIPROCESS.2016.7888262","url":null,"abstract":"The interference of noise used to depredate the performance of the conventional time-domain back-projection (BP) imaging method. In this letter, a projection imaging method is proposed for noise suppression. The proposed method utilizes the symmetry of the cross-correlation function of the ideal echo signal and the realistic one to suppress the interference of noise. The performance of the proposed method is experimentally investigated in comparison to that of the conventional time-domain back-projection (BP) method. The results show that the proposed method outperforms the conventional BP method for noise suppression.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129467900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Sparse linear array three-dimensional imaging approach based on compressed sensing 基于压缩感知的稀疏线阵三维成像方法
2016 IEEE International Conference on Signal and Image Processing (ICSIP) Pub Date : 2016-08-01 DOI: 10.1109/SIPROCESS.2016.7888271
Xin Tan, Yang Fang, Xiaoyi Feng, Wei Cheng, Baoping Wang
{"title":"Sparse linear array three-dimensional imaging approach based on compressed sensing","authors":"Xin Tan, Yang Fang, Xiaoyi Feng, Wei Cheng, Baoping Wang","doi":"10.1109/SIPROCESS.2016.7888271","DOIUrl":"https://doi.org/10.1109/SIPROCESS.2016.7888271","url":null,"abstract":"With regard to the problems of traditional sparse array antenna imaging approach, since azimuth sampling insufficient of echo signal, it will cause poor resolution such as low resolution, serious main lobe expansion and side lobe jamming, 3D imaging approach of sparse array antenna based on compressed sensing is proposed. Based on Linear array antenna mode, sparse banded observer is designed, and then down-sampling is realized. CoSAMP algorithm is adopted to realize high-resolution image reconstruction. Testing platform is set up in microwave anechoic chamber. Target echo data are obtained through planar array antenna scanning, and then 3D imaging is conducted for targets, which verifies the validity of algorithm. The results show that, in sparse array, the proposed imaging approach has higher imaging resolution.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129575162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Cartoon image segmentation based on improved SLIC superpixels and adaptive region propagation merging 基于改进SLIC超像素和自适应区域传播合并的卡通图像分割
2016 IEEE International Conference on Signal and Image Processing (ICSIP) Pub Date : 2016-08-01 DOI: 10.1109/SIPROCESS.2016.7888267
Huisi Wu, Yilin Wu, Shenglong Zhang, Ping Li, Zhenkun Wen
{"title":"Cartoon image segmentation based on improved SLIC superpixels and adaptive region propagation merging","authors":"Huisi Wu, Yilin Wu, Shenglong Zhang, Ping Li, Zhenkun Wen","doi":"10.1109/SIPROCESS.2016.7888267","DOIUrl":"https://doi.org/10.1109/SIPROCESS.2016.7888267","url":null,"abstract":"This paper present a novel algorithm for cartoon image segmentation based on the simple linear iterative clustering (SLIC) superpixels and adaptive region propagation merging. To break the limitation of the original SLIC algorithm in confirming to image boundaries, this paper proposed to improve the quality of the superpixels generation based on the connectivity constraint. To achieve efficient segmentation from the superpixels, this paper employed an adaptive region propagation merging algorithm to obtain independent segmented object. Compared with the pixel-based segmentation algorithms and other superpixel-based segmentation methods, the method proposed in this paper is more effective and more efficient by determining the propagation center adaptively. Experiments on abundant cartoon images showed that our algorithm outperforms classical segmentation algorithms with the boundary-based and region-based criteria. Furthermore, the final cartoon image segmentation results are also well consistent with the human visual perception.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131476059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 20
Over-the-horizon time and frequency synchronization for maneuverable radar system based on troposcatter 基于对流层散射的机动雷达系统超视距时频同步
2016 IEEE International Conference on Signal and Image Processing (ICSIP) Pub Date : 2016-08-01 DOI: 10.1109/SIPROCESS.2016.7888309
Chenglong Li, Xihong Chen, Zan Liu
{"title":"Over-the-horizon time and frequency synchronization for maneuverable radar system based on troposcatter","authors":"Chenglong Li, Xihong Chen, Zan Liu","doi":"10.1109/SIPROCESS.2016.7888309","DOIUrl":"https://doi.org/10.1109/SIPROCESS.2016.7888309","url":null,"abstract":"Time and frequency synchronization is prerequisite of coordinating multi-static radar system. However, available synchronization methods do not provide practical beyond line-of-sight synchronization especially under the condition of maneuver. Therefore, a novel time and frequency synchronization mechanism based on troposcatter has been proposed. And the main motivations of this paper are to analyze and calculate the main time delay errors, including equipment delay errors and path time delay errors, in the process of time signal transmission and calibration. The result indicates that, the time delay errors of the proposed synchronization method fulfill the requirement of beyond line-of-sight time and frequency synchronization for maneuverable radar system.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127667772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信