Pub Date : 2016-10-01DOI: 10.1109/CISP-BMEI.2016.7852918
L. Yin, M. Xie, Haidi Li, Chao Wang, Xiongjun Fu
Digital radio frequency memory (DRFM) is an important part of modern electronic jamming equipment. It achieves high fidelity in the storage of radar waveform and guarantees the coherence between interference and radar signal. In this paper, a design scheme of the DRFM system based on FPGA and DSP is proposed, and the FPGA is the vital part of it. According to the complex FPGA function and high design challenge, an architecture based on advanced extensible interface 4.0 (AXI4) used to build the embedded system on FPGA is presented, which greatly enhances the flexibility of the system, speeds up the development, and brings conveniences for upgrade and maintenance.
{"title":"Design and implementation of the digital radio frequency memory system based on advanced extensible interface 4.0","authors":"L. Yin, M. Xie, Haidi Li, Chao Wang, Xiongjun Fu","doi":"10.1109/CISP-BMEI.2016.7852918","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2016.7852918","url":null,"abstract":"Digital radio frequency memory (DRFM) is an important part of modern electronic jamming equipment. It achieves high fidelity in the storage of radar waveform and guarantees the coherence between interference and radar signal. In this paper, a design scheme of the DRFM system based on FPGA and DSP is proposed, and the FPGA is the vital part of it. According to the complex FPGA function and high design challenge, an architecture based on advanced extensible interface 4.0 (AXI4) used to build the embedded system on FPGA is presented, which greatly enhances the flexibility of the system, speeds up the development, and brings conveniences for upgrade and maintenance.","PeriodicalId":275095,"journal":{"name":"2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117139952","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}
Pub Date : 2016-10-01DOI: 10.1109/CISP-BMEI.2016.7852676
Hang Chen, Dongfang Chen, Xiaofeng Wang
In order to solve the problems of object detection and object tracking under complex scenes in video, this paper proposes a way to improve Gaussian Mixture Model algorithm based on the traditional Gaussian Mixture Model. When the model is updated, according to the characteristics of continuous video frame, the background model is divided into static regions and dynamic regions, and the background is updated in different strategies. Then, this paper presents an algorithm for the intrusion detection. Intrusion is judged by whether the centroid of the target is in the specific area. If the centroid is located outside the area, it shows that the target does not invade the specific area, otherwise the target invades the specific area. If so, the system triggers alarm and label information appear on the video frames. Experiments show that this algorithm can realize the intrusion detection of specific area.
{"title":"Intrusion detection of specific area based on video","authors":"Hang Chen, Dongfang Chen, Xiaofeng Wang","doi":"10.1109/CISP-BMEI.2016.7852676","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2016.7852676","url":null,"abstract":"In order to solve the problems of object detection and object tracking under complex scenes in video, this paper proposes a way to improve Gaussian Mixture Model algorithm based on the traditional Gaussian Mixture Model. When the model is updated, according to the characteristics of continuous video frame, the background model is divided into static regions and dynamic regions, and the background is updated in different strategies. Then, this paper presents an algorithm for the intrusion detection. Intrusion is judged by whether the centroid of the target is in the specific area. If the centroid is located outside the area, it shows that the target does not invade the specific area, otherwise the target invades the specific area. If so, the system triggers alarm and label information appear on the video frames. Experiments show that this algorithm can realize the intrusion detection of specific area.","PeriodicalId":275095,"journal":{"name":"2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116262920","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}
Pub Date : 2016-10-01DOI: 10.1109/CISP-BMEI.2016.7852941
Xin-Yue Li, Fan Xu, Xiao Hu, Shao-Hu Peng, H. Nam, Jin-Ming Zhao
Segmentation for pulmonary parenchyma is a crucial step for computer aided diagnosis (CAD) systems. The accuracy of pulmonary parenchyma segmentation can have a great impact on further steps of CAD systems, such as pulmonary nodule detection and feature extraction. Before segmentation, preprocessing should be done to remove references outside the thorax. After preprocessing, pulmonary parenchyma area threshold will be employed to realize segmentation. However, current segmentation approaches are mainly based on a fixed area threshold, which confronts problem of mis-segmentation and high segmentation failure rate. This article proposed a novel self-adapting threshold segmentation approach, which realized fully automatic segmentation and held considerable accuracy rate. First, fitting of polynomials based on the least square law is constructed to fit curves of pulmonary parenchyma areas. Secondly, a golden standard is created to represent change trend of pulmonary parenchyma for all patients. Finally, the golden standard is adjusted accordingly to realize full adaption and automation of segmentation. Experimental results indicated that the proposed approach achieved excellent accuracy rate and precise segmentation.
{"title":"Self-adapting threshold of pulmonary parenchyma","authors":"Xin-Yue Li, Fan Xu, Xiao Hu, Shao-Hu Peng, H. Nam, Jin-Ming Zhao","doi":"10.1109/CISP-BMEI.2016.7852941","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2016.7852941","url":null,"abstract":"Segmentation for pulmonary parenchyma is a crucial step for computer aided diagnosis (CAD) systems. The accuracy of pulmonary parenchyma segmentation can have a great impact on further steps of CAD systems, such as pulmonary nodule detection and feature extraction. Before segmentation, preprocessing should be done to remove references outside the thorax. After preprocessing, pulmonary parenchyma area threshold will be employed to realize segmentation. However, current segmentation approaches are mainly based on a fixed area threshold, which confronts problem of mis-segmentation and high segmentation failure rate. This article proposed a novel self-adapting threshold segmentation approach, which realized fully automatic segmentation and held considerable accuracy rate. First, fitting of polynomials based on the least square law is constructed to fit curves of pulmonary parenchyma areas. Secondly, a golden standard is created to represent change trend of pulmonary parenchyma for all patients. Finally, the golden standard is adjusted accordingly to realize full adaption and automation of segmentation. Experimental results indicated that the proposed approach achieved excellent accuracy rate and precise segmentation.","PeriodicalId":275095,"journal":{"name":"2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115263226","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}
Pub Date : 2016-10-01DOI: 10.1109/CISP-BMEI.2016.7852746
Xiaoming Liu, Jia Wang, Zhou Yang
Many distinguished methods for vascular network detection in fundus images were proposed to help the diagnosis of clinical diseases. The vascular bifurcation sample in OCT projection images is quite limited while it is sufficient in the corresponding fundus images. In this paper, we proposed a transfer learning-based method to detect the vascular bifurcations in OCT projection images using supervised transfer learning method. The samples from fundus images are utilized with transfer learning technique for vascular bifurcations detection in OCT projection images. The experimental results show the accuracy of vascular bifurcations detection can be improved by the proposed method.
{"title":"A vascular bifurcations detection method based on Transfer Learning model","authors":"Xiaoming Liu, Jia Wang, Zhou Yang","doi":"10.1109/CISP-BMEI.2016.7852746","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2016.7852746","url":null,"abstract":"Many distinguished methods for vascular network detection in fundus images were proposed to help the diagnosis of clinical diseases. The vascular bifurcation sample in OCT projection images is quite limited while it is sufficient in the corresponding fundus images. In this paper, we proposed a transfer learning-based method to detect the vascular bifurcations in OCT projection images using supervised transfer learning method. The samples from fundus images are utilized with transfer learning technique for vascular bifurcations detection in OCT projection images. The experimental results show the accuracy of vascular bifurcations detection can be improved by the proposed method.","PeriodicalId":275095,"journal":{"name":"2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115490544","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}
Pub Date : 2016-10-01DOI: 10.1109/CISP-BMEI.2016.7852891
Lian-qing Yu, Huan Zhu, Si-ming Li, Yu-Hao Yang
Based on the division or partition of sub array of airborne early warning (AEW) radar, a new method for the partition of the sub array is proposed, which is based on the path search of the directed graph. Under the condition that the number of sub array is given, to maximize the improved factor of sub array level STAP and the lowest side-lobe are the optimization criterion, which is used to search the optimal sub array. Finally, comparing research with other methods is also presented, and the simulation results demonstrate the efficacy of the proposed methods.
{"title":"An optimal sub array partitioning method based on directed graph path search","authors":"Lian-qing Yu, Huan Zhu, Si-ming Li, Yu-Hao Yang","doi":"10.1109/CISP-BMEI.2016.7852891","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2016.7852891","url":null,"abstract":"Based on the division or partition of sub array of airborne early warning (AEW) radar, a new method for the partition of the sub array is proposed, which is based on the path search of the directed graph. Under the condition that the number of sub array is given, to maximize the improved factor of sub array level STAP and the lowest side-lobe are the optimization criterion, which is used to search the optimal sub array. Finally, comparing research with other methods is also presented, and the simulation results demonstrate the efficacy of the proposed methods.","PeriodicalId":275095,"journal":{"name":"2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123595925","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}
Pub Date : 2016-10-01DOI: 10.1109/CISP-BMEI.2016.7852931
Fan Xu, Wen-Jing Zhang, Xin-Yue Li, Hu Xiao, Shao-Hu Peng, H. Nam, M. Zhang
The computer-aided diagnostic (CAD) system can greatly influence the early detection of lung cancer in radiographs and computed tomography (CT) images. And the automatic nodule detection plays an important role in the CAD systems. This paper proposed a new enhancement filter (3D multi-scale Block LBP Filter) to detect the nodules in the lung regions. By taking advantages of the nodule regions' pixel value characteristics and shape features, the proposed filter is able to enhance the nodule-like regions and restrain the line-like regions and edge regions. Moreover, Integral Image Technique (IIT) is applied accelerate the processing speed of the filter. Experimental results showed that the proposed filter can improve the accuracy and reduce the false positive.
{"title":"A 3D multi-scale Block LBP Filter for lung nodule enhancement based on the CT images","authors":"Fan Xu, Wen-Jing Zhang, Xin-Yue Li, Hu Xiao, Shao-Hu Peng, H. Nam, M. Zhang","doi":"10.1109/CISP-BMEI.2016.7852931","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2016.7852931","url":null,"abstract":"The computer-aided diagnostic (CAD) system can greatly influence the early detection of lung cancer in radiographs and computed tomography (CT) images. And the automatic nodule detection plays an important role in the CAD systems. This paper proposed a new enhancement filter (3D multi-scale Block LBP Filter) to detect the nodules in the lung regions. By taking advantages of the nodule regions' pixel value characteristics and shape features, the proposed filter is able to enhance the nodule-like regions and restrain the line-like regions and edge regions. Moreover, Integral Image Technique (IIT) is applied accelerate the processing speed of the filter. Experimental results showed that the proposed filter can improve the accuracy and reduce the false positive.","PeriodicalId":275095,"journal":{"name":"2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124682204","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}
Pub Date : 2016-10-01DOI: 10.1109/CISP-BMEI.2016.7852812
C. Zhao, Hongbo Bi, Y. Liu, Ning Li
Traditional digital watermarking in transform domain computes complex and has limited anti-attack. Different ways of signal sparsity of compressed sensing represent different domains, which expands the embeddable space of watermarking. To take advantage of its multi-direction and multi-resolution characteristics to sparse image, Contourlet transform was analyzed. For the limitation of traditional block decision, we adopt the interleaving extraction to reduce the block artifacts. Furthermore, we presented the watermarking algorithm based on interleaving extraction block compressed sensing in Contourlet domain, simulation results verifies that the algorithm enhances the peak signal to noise ratio. Attack tests show that the proposed digital watermarking has better robustness against JPEG compression, noising, cutting etc.
{"title":"Digital watermarking based on interleaving extraction block compressed sensing in Contourlet domain","authors":"C. Zhao, Hongbo Bi, Y. Liu, Ning Li","doi":"10.1109/CISP-BMEI.2016.7852812","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2016.7852812","url":null,"abstract":"Traditional digital watermarking in transform domain computes complex and has limited anti-attack. Different ways of signal sparsity of compressed sensing represent different domains, which expands the embeddable space of watermarking. To take advantage of its multi-direction and multi-resolution characteristics to sparse image, Contourlet transform was analyzed. For the limitation of traditional block decision, we adopt the interleaving extraction to reduce the block artifacts. Furthermore, we presented the watermarking algorithm based on interleaving extraction block compressed sensing in Contourlet domain, simulation results verifies that the algorithm enhances the peak signal to noise ratio. Attack tests show that the proposed digital watermarking has better robustness against JPEG compression, noising, cutting etc.","PeriodicalId":275095,"journal":{"name":"2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124111687","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}
Pub Date : 2016-10-01DOI: 10.1109/CISP-BMEI.2016.7852672
Rongfeng Zhang, Huanhou Xiao, Ting Deng, Wei Qiu, Jinglun Shi
Visual tracking is one of the hot research topics in computer vision in recent years. It has been widely used in many vision applications, such as traffic surveillance, anti-terrorism. However, there are still challenges for visual tracking, like illumination change, object occlusion, appearance deformation, etc. This paper proposes a robust point detection algorithm based on wavelet transform for visual tracking. First, the input image patch that includes the tracking object is decomposed by wavelet transform with several levels and the wavelet coefficients are obtained. The wavelet coefficients are then analyzed and the points that hold the local maximal wavelet coefficients are determined as the robust points for tracking. Finally, the proposed method is integrated to the Tracking Learning Detection (TLD) framework, which not only improves the tracking precision, but also reduces the false detection. Experimental results showed that the new algorithm outperformed the TLD method with respect to the precision, recall, and f-measure.
{"title":"A robust point detection algorithm based on wavelet transform for visual tracking","authors":"Rongfeng Zhang, Huanhou Xiao, Ting Deng, Wei Qiu, Jinglun Shi","doi":"10.1109/CISP-BMEI.2016.7852672","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2016.7852672","url":null,"abstract":"Visual tracking is one of the hot research topics in computer vision in recent years. It has been widely used in many vision applications, such as traffic surveillance, anti-terrorism. However, there are still challenges for visual tracking, like illumination change, object occlusion, appearance deformation, etc. This paper proposes a robust point detection algorithm based on wavelet transform for visual tracking. First, the input image patch that includes the tracking object is decomposed by wavelet transform with several levels and the wavelet coefficients are obtained. The wavelet coefficients are then analyzed and the points that hold the local maximal wavelet coefficients are determined as the robust points for tracking. Finally, the proposed method is integrated to the Tracking Learning Detection (TLD) framework, which not only improves the tracking precision, but also reduces the false detection. Experimental results showed that the new algorithm outperformed the TLD method with respect to the precision, recall, and f-measure.","PeriodicalId":275095,"journal":{"name":"2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124526258","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}
Pub Date : 2016-10-01DOI: 10.1109/CISP-BMEI.2016.7852964
Rui Xing, N. Dai, Yicheng Zhong, Yihua Zhang, Yi Liu
In the process of orthodontic treatment, in order to make patients adorn appropriate brackets fast and accurately, this paper proposes a new modeling method of customized brackets and individualized trays. First of all, as the straight-wire can smoothly pass through all bracket slots after orthodontic treatment, bracket bodies in the database are positioned to the tooth surfaces automatically. Then some of them may be adjusted manually in accordance with specific conditions. Subsequently, customized brackets are designed based on the teeth morphology of patient. Finally, we can create each individualized tray rapidly on the basis of isometric extrude operation and Boolean operation. Some experiments have been tested by 3D printing technology and modeling platform. The results proved that the proposed modeling method has higher efficiency and the bonded bracket positioning is accurate and reliable.
{"title":"A modeling method of customized brackets and individualized trays for orthodontic treatment","authors":"Rui Xing, N. Dai, Yicheng Zhong, Yihua Zhang, Yi Liu","doi":"10.1109/CISP-BMEI.2016.7852964","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2016.7852964","url":null,"abstract":"In the process of orthodontic treatment, in order to make patients adorn appropriate brackets fast and accurately, this paper proposes a new modeling method of customized brackets and individualized trays. First of all, as the straight-wire can smoothly pass through all bracket slots after orthodontic treatment, bracket bodies in the database are positioned to the tooth surfaces automatically. Then some of them may be adjusted manually in accordance with specific conditions. Subsequently, customized brackets are designed based on the teeth morphology of patient. Finally, we can create each individualized tray rapidly on the basis of isometric extrude operation and Boolean operation. Some experiments have been tested by 3D printing technology and modeling platform. The results proved that the proposed modeling method has higher efficiency and the bonded bracket positioning is accurate and reliable.","PeriodicalId":275095,"journal":{"name":"2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124984913","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}
Pub Date : 2016-10-01DOI: 10.1109/CISP-BMEI.2016.7852780
L. Zhong, W. Luo, Lianru Gao
Spectral unmixing is an important technique for hyperspectral data exploring. Recently the nonlinear unmixing technique which considers the nonlinear mixing terms becomes an important issue of spectral unmixing. Here, we consider a particle swarm optimization technique for nonlinear unmixing. Our motivation is to make a first step to exploit the potential capability of PSO for nonlinear unmixing. The proposed algorithm does not need any prior information concerning about the gradient or hessian matrix. Therefore, it can be easily applied to characterize complex nonlinear mixtures. In addition, it provides a stochastic mechanism that can improve the probability to find a better solution. Furthermore, the experimental results indicate that our algorithm can outperform the traditional algorithm for both synthetic and real hyperspectral data.
{"title":"A particle swarm optimization algorithm for unmixing the polynomial post-nonlinear mixing model","authors":"L. Zhong, W. Luo, Lianru Gao","doi":"10.1109/CISP-BMEI.2016.7852780","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2016.7852780","url":null,"abstract":"Spectral unmixing is an important technique for hyperspectral data exploring. Recently the nonlinear unmixing technique which considers the nonlinear mixing terms becomes an important issue of spectral unmixing. Here, we consider a particle swarm optimization technique for nonlinear unmixing. Our motivation is to make a first step to exploit the potential capability of PSO for nonlinear unmixing. The proposed algorithm does not need any prior information concerning about the gradient or hessian matrix. Therefore, it can be easily applied to characterize complex nonlinear mixtures. In addition, it provides a stochastic mechanism that can improve the probability to find a better solution. Furthermore, the experimental results indicate that our algorithm can outperform the traditional algorithm for both synthetic and real hyperspectral data.","PeriodicalId":275095,"journal":{"name":"2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"135 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131108923","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}
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