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2015 8th International Congress on Image and Signal Processing (CISP)最新文献

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Realization of standard distortion source based on the function signal generator 基于函数信号发生器的标准失真源的实现
2015 8th International Congress on Image and Signal Processing (CISP) Pub Date : 2015-10-01 DOI: 10.1109/CISP.2015.7408142
Yue Wang, Hongguang Xu, Tong Qin, Yuehong Jin, Nuo Li
{"title":"Realization of standard distortion source based on the function signal generator","authors":"Yue Wang, Hongguang Xu, Tong Qin, Yuehong Jin, Nuo Li","doi":"10.1109/CISP.2015.7408142","DOIUrl":"https://doi.org/10.1109/CISP.2015.7408142","url":null,"abstract":"This thesis introduces a digital method which can generate standard distortion signal. Based on the mathematical definition of distortion, standard distortion signals with fixed distortion are generated by Matlab, and then downloaded to the function signal generator. At last the standard signal distortion is output by the function signal generator. In addition, this paper introduces the realization of the distortion measurement calibration system. The method introduced in this thesis is verified successfully with audio analyzer, and the related experimental results are also given to the readers. In order to solve the problem that most of distortion sources are heavy and can not be programmed to control, this method which has broad application prospects uses only one function signal generator can complete to output 0.5% and above arbitrary standard distortion signals.","PeriodicalId":167631,"journal":{"name":"2015 8th International Congress on Image and Signal Processing (CISP)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121082191","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
Intelligent image retrieval of visual cultural symbols 视觉文化符号的智能图像检索
2015 8th International Congress on Image and Signal Processing (CISP) Pub Date : 2015-10-01 DOI: 10.1109/CISP.2015.7407941
Beibei Zhu, Xiaoyu Wu, Lei Yang, Yan He
{"title":"Intelligent image retrieval of visual cultural symbols","authors":"Beibei Zhu, Xiaoyu Wu, Lei Yang, Yan He","doi":"10.1109/CISP.2015.7407941","DOIUrl":"https://doi.org/10.1109/CISP.2015.7407941","url":null,"abstract":"The retrieval of visual cultural symbols is an important research field of inheriting and carrying forward Chinese traditional culture in digital way. Generally visual cultural symbols are foregrounds of natural images, so using shape features in image retrieval that needs image segmentation in advance has great advantages. At present, image segmentation is mostly interactive, which is quite subjective, and it also takes a tremendous amount of work to process a large number of images. Therefore this paper proposed an intelligent image retrieval that combined the saliency region segmentation algorithm based on K-means clustering with the improved shape context. It showed good retrieval results on both property and efficiency.","PeriodicalId":167631,"journal":{"name":"2015 8th International Congress on Image and Signal Processing (CISP)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122562738","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
Focusing algorithm based on droplet measurement 基于液滴测量的聚焦算法
2015 8th International Congress on Image and Signal Processing (CISP) Pub Date : 2015-10-01 DOI: 10.1109/CISP.2015.7407905
Bao-Chun Li, Meng Huang
{"title":"Focusing algorithm based on droplet measurement","authors":"Bao-Chun Li, Meng Huang","doi":"10.1109/CISP.2015.7407905","DOIUrl":"https://doi.org/10.1109/CISP.2015.7407905","url":null,"abstract":"In-line digital hologram can realize particle detection in space of 3D coordinate. The in-line digital hologram is based on the coherent light imaging theory. When the distance of reconstruction deviate from the focus, we find the edge of the reconstructed image will appear a lot of stripes caused by diffraction. The traditional evaluation method is to focus on the image directly. It will not be able to get the correct position, and can't get accurate particle three-dimensional of space. In this paper, it is based on the detection of laboratory cloud droplets particles to research the focus plane position of reconstructed image.","PeriodicalId":167631,"journal":{"name":"2015 8th International Congress on Image and Signal Processing (CISP)","volume":"471 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122894150","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
Analysis of phase diversity jamming signal for pulse compression radar 脉冲压缩雷达相分集干扰信号分析
2015 8th International Congress on Image and Signal Processing (CISP) Pub Date : 2015-10-01 DOI: 10.1109/CISP.2015.7408100
Daobin Yu, Hongyan Wang, Jin-ao Yu
{"title":"Analysis of phase diversity jamming signal for pulse compression radar","authors":"Daobin Yu, Hongyan Wang, Jin-ao Yu","doi":"10.1109/CISP.2015.7408100","DOIUrl":"https://doi.org/10.1109/CISP.2015.7408100","url":null,"abstract":"The design and analysis of radar jamming signal is a main stream in radar countermeasures' study. This paper proposes a method by using phase diversity processing, and the process of jamming signal's generation is elaborated in details. The frequency spectrum of the signal is derived after that, and the ambiguity function is used as a tool to analyze the characteristic of the jamming signal. Finally, the simulation is conducted to prove the conclusion above, and it is obvious that the jamming signal has great advantages in its nature.","PeriodicalId":167631,"journal":{"name":"2015 8th International Congress on Image and Signal Processing (CISP)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123881286","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 mapping method of image mosaic algorithm on embedded reconfigurable processor 嵌入式可重构处理器上图像拼接算法的映射方法
2015 8th International Congress on Image and Signal Processing (CISP) Pub Date : 2015-10-01 DOI: 10.1109/CISP.2015.7407995
Jingbo Wang, Zaifeng Shi, Ke Pang, Tianye Gao, Qingjie Cao
{"title":"A mapping method of image mosaic algorithm on embedded reconfigurable processor","authors":"Jingbo Wang, Zaifeng Shi, Ke Pang, Tianye Gao, Qingjie Cao","doi":"10.1109/CISP.2015.7407995","DOIUrl":"https://doi.org/10.1109/CISP.2015.7407995","url":null,"abstract":"A mapping method of image mosaic algorithm based on Reconfigurable Processing Element Array (RPEA) is proposed. This method can effectively improve the utilization rate of parallel resources. In the image mosaic algorithm, Harris corner detection is used to extract the feature points. Normalized Cross Correlation (NCC) algorithm is used to match these feature points and Random sample consensus (RANSAC) algorithm is used to eliminate the mismatching. Critical parts of the algorithms described in C language are found out, which are dynamically mapped onto the RPEA to run concurrently. The execution time on RPEA is reported to compare with execution time on general single-core processor. This paper focuses on the mapping methods based on loop unrolling and software pipeline loop and proposes an optimized method. The test results show that the speedups of mapping the mosaic algorithm on the reconfigurable processor with the proposed method versus using Intel Atom 230 reach more than 2.","PeriodicalId":167631,"journal":{"name":"2015 8th International Congress on Image and Signal Processing (CISP)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125183838","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
Signal recognition of the optical fiber vibration sensor based on two-level feature extraction 基于两级特征提取的光纤振动传感器信号识别
2015 8th International Congress on Image and Signal Processing (CISP) Pub Date : 2015-10-01 DOI: 10.1109/CISP.2015.7408118
Liang Wang, Yubin Guo, T. Sun, Jiayu Huo, Le Zhang
{"title":"Signal recognition of the optical fiber vibration sensor based on two-level feature extraction","authors":"Liang Wang, Yubin Guo, T. Sun, Jiayu Huo, Le Zhang","doi":"10.1109/CISP.2015.7408118","DOIUrl":"https://doi.org/10.1109/CISP.2015.7408118","url":null,"abstract":"To deal with the high false alarm rate in optical fiber Michelson interferometer, a two-level feature extraction algorithm based on threshold-crossing rate and sparse auto-encoders is proposed. The threshold-crossing rate algorithm is used as the first level feature extraction to identify whether vibration occurs. If vibrations occur, the sparse auto-encoders algorithm is applied to extract high dimension features of vibration signals, and then the extraction feature will be sent to a classifier to recognize vibration pattern. Experiment results show that this method can effectively identify five kinds of vibrations and reduce false rate.","PeriodicalId":167631,"journal":{"name":"2015 8th International Congress on Image and Signal Processing (CISP)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125377963","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: 10
A robust image reconstruction based on convex combination of criteria 基于凸组合准则的鲁棒图像重建
2015 8th International Congress on Image and Signal Processing (CISP) Pub Date : 2015-10-01 DOI: 10.1109/CISP.2015.7407998
Y. Xia, Wenyao Xia
{"title":"A robust image reconstruction based on convex combination of criteria","authors":"Y. Xia, Wenyao Xia","doi":"10.1109/CISP.2015.7407998","DOIUrl":"https://doi.org/10.1109/CISP.2015.7407998","url":null,"abstract":"In this paper we propose a novel regularization method for robust image reconstruction against noise, based on convex combination of the least squares and least absolute deviations. Unlike conventional regularization methods with an assumption of Guaussian noise, the proposed regularization method can deal with Gaussian noise and non-Gaussian noise. To overcome difficulty of the non-smooth objective function, we develop an efficient sub-gradient algorithm. Computed examples with an application to MR images show that the proposed subgradient algorithm can give better reconstruction quality than the conventional reconstruction regularization algorithms in various noise.","PeriodicalId":167631,"journal":{"name":"2015 8th International Congress on Image and Signal Processing (CISP)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125754633","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
Classification of dominant tree species in an urban forest park using the remote sensing image of WorldView-2 基于WorldView-2遥感影像的城市森林公园优势树种分类
2015 8th International Congress on Image and Signal Processing (CISP) Pub Date : 2015-10-01 DOI: 10.1109/CISP.2015.7407976
Chao Yu, Mingyang Li, M. Zhang
{"title":"Classification of dominant tree species in an urban forest park using the remote sensing image of WorldView-2","authors":"Chao Yu, Mingyang Li, M. Zhang","doi":"10.1109/CISP.2015.7407976","DOIUrl":"https://doi.org/10.1109/CISP.2015.7407976","url":null,"abstract":"There are many land use types and tree species in urban forest parks in which the human disturbance is frequent. Using remote sensing images to estimate the main tree species may provide a scientific basis for the making of sustainable management measures for scenic forest. In this article, Zijin Mountain National Forest Park in Nanjing, China, was selected as the case study area, and WorldView-2 data in December 2011 was chosen as the main information sources. Three kinds of band combinations were compared by using index of classification accuracy. Then the optimal combination was used to do supervised classification through three classification methods of decision tree classifier, neural networks, and support vector machine classification to distinguish the land use and the main species in the study area. The results showed that:1)The classification accuracy of 8-band combination of WorldView-2 is the highest and the overall accuracy and Kappa coefficients are 80.81% and 0.77, respectively, followed by the new 4-band combination and the standard 4-band combination. 2) Using the 8-band combination, the performance of decision tree classification is the best with overall classification accuracy of 87.10% and Kappa coefficient of 0.85, while the performance of neural networks classification is the worst with overall classification accuracy of 73.85% and Kappa coefficient of 0.70. 3) When comparing the accuracy of different tree species using decision tree classification, classification accuracy of the major local species is high, while the accuracy of foreign pine and cypress is relatively low.","PeriodicalId":167631,"journal":{"name":"2015 8th International Congress on Image and Signal Processing (CISP)","volume":"256 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126048428","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
Computational methods for the identification of mature microRNAs within their Pre-miRNA 在Pre-miRNA中鉴定成熟microrna的计算方法
2015 8th International Congress on Image and Signal Processing (CISP) Pub Date : 2015-10-01 DOI: 10.1109/CISP.2015.7408071
Ying Wang, Xuefeng Dai, Jidong Ru, Dan Lv, Jin Li
{"title":"Computational methods for the identification of mature microRNAs within their Pre-miRNA","authors":"Ying Wang, Xuefeng Dai, Jidong Ru, Dan Lv, Jin Li","doi":"10.1109/CISP.2015.7408071","DOIUrl":"https://doi.org/10.1109/CISP.2015.7408071","url":null,"abstract":"The urgent demand in miRNA research has call for the high performance computational methods for mature miRNA identification to supplement the biological experiment methods. In this study, we analyzed the secondary structure of pre-miRNA and extracted the important features. Then the current computational methods are investigated, and the flow chart of mature miRNAs location prediction methods is summarized. In addition, the current methods and algorithms are classified and assessed. Notably, we compare five machine learning algorithms of Naive Bayes, SVM, Random Forest, the Conditional Random Field and Adaboosting for mature miRNA-located prediction. Empirical findings indicated that SVM algorithm could achieve better performance than Naive Bayes method. And the Random Forest method is comparable to the performance of SVM, it shows good performance in this subject.","PeriodicalId":167631,"journal":{"name":"2015 8th International Congress on Image and Signal Processing (CISP)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126069341","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 classifier of satellite signals based on the back-propagation neural network 基于反向传播神经网络的卫星信号分类器
2015 8th International Congress on Image and Signal Processing (CISP) Pub Date : 2015-10-01 DOI: 10.1109/CISP.2015.7408093
Wei Zhang, Zhong Li, Weidong Xu, Haiquan Zhou
{"title":"A classifier of satellite signals based on the back-propagation neural network","authors":"Wei Zhang, Zhong Li, Weidong Xu, Haiquan Zhou","doi":"10.1109/CISP.2015.7408093","DOIUrl":"https://doi.org/10.1109/CISP.2015.7408093","url":null,"abstract":"In order to achieve the fast classification for Ultra-low-frequency (ULF) electron field data in the Space, this paper designs an electric field classifier based on the back-propagation (BP) neural network with extracting the ULF section electric field waveform data of the Wenchuan earthquake, using the statistical methods to obtain four characteristics of the mean value, mean square error, skewness and kurtosis of an electric field components. Its findings are summarized as follows: (1) This classifier of electric signals is effective with normal data and abnormal data accounting for 72.3% and 27.7% respectively; (2) A momentum factor can improve effectively the BP network performance, which the momentum factor is smaller, the network convergence speed is faster; (3) An adaptive learning factor can reduce effectively the target error. This method is also suitable for the data classification of magnetic field and ion concentration to obtain the seismic precursor knowledge, which has the practical significance for earthquake monitoring and prediction.","PeriodicalId":167631,"journal":{"name":"2015 8th International Congress on Image and Signal Processing (CISP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130121521","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: 7
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