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2016 IEEE 13th International Conference on Signal Processing (ICSP)最新文献

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Adaptive angle-Doppler compensation in airborne phased radar for planar array 平面阵机载相控雷达自适应角-多普勒补偿
2016 IEEE 13th International Conference on Signal Processing (ICSP) Pub Date : 2016-11-01 DOI: 10.1109/ICSP.2016.7878093
Fengde Jia, Zishu He, Jun Yu Li, Junhui Qian
{"title":"Adaptive angle-Doppler compensation in airborne phased radar for planar array","authors":"Fengde Jia, Zishu He, Jun Yu Li, Junhui Qian","doi":"10.1109/ICSP.2016.7878093","DOIUrl":"https://doi.org/10.1109/ICSP.2016.7878093","url":null,"abstract":"Space-time adaptive processing (STAP) is widely applied in airborne planar array phased radar to suppress clutter or interference, especially range ambiguous clutter. This approach requires an accurate estimation of clutter covariance matrix(CCM) by the secondary data snapshots. However, in the forward-looking scenario angle-Doppler relationship is severely range-dependent(i.e clutter nonstationarity), even worse in down-looking scenario. This phenomenon makes the CCM inaccurate, and the STAP performance will be degraded badly. In this paper, we perform a planar adaptive angle-Doppler compensation(P-A2DC) on the clutter training snapshots. “Adaptive” means it's unnecessary to have a prior knowledge of system measurements, which maybe erroneous or missing. Besides, the planar array has an extra elevation resolution, so the compensation is three-dimensional. The simulations follows show that P-A2DC can receive promising performance.","PeriodicalId":234499,"journal":{"name":"2016 IEEE 13th International Conference on Signal Processing (ICSP)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128138589","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
Image watermarking scheme based on Arnold transform and DWT-DCT-SVD 基于Arnold变换和DWT-DCT-SVD的图像水印方案
2016 IEEE 13th International Conference on Signal Processing (ICSP) Pub Date : 2016-11-01 DOI: 10.1109/ICSP.2016.7877942
Zhi Zhang, Chengyou Wang, Xiao Zhou
{"title":"Image watermarking scheme based on Arnold transform and DWT-DCT-SVD","authors":"Zhi Zhang, Chengyou Wang, Xiao Zhou","doi":"10.1109/ICSP.2016.7877942","DOIUrl":"https://doi.org/10.1109/ICSP.2016.7877942","url":null,"abstract":"In this paper, an improved digital watermarking scheme combined with multi-level discrete cosine transform (DCT), discrete wavelet transform (DWT), and singular value decomposition (SVD) is proposed. To improve the security of the watermark, the encrypted watermark is acquired by Arnold transform before watermark embedding. The proposed scheme is proved to be robust, and its performance is evaluated with respect to the normalized correlation (NC) and peak signal-to-noise ratio (PSNR). The robustness of the proposed scheme is also evaluated under different attacks which include salt and pepper noise, Gaussian noise, and other attacks. The experimental results are also conducted to verify the effect of false positive problem which exists in most watermarking schemes based on SVD.","PeriodicalId":234499,"journal":{"name":"2016 IEEE 13th International Conference on Signal Processing (ICSP)","volume":"356 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125643252","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: 24
Fusing deep convolutional network with SFM for 3D face reconstruction 融合深度卷积网络与SFM的三维人脸重建
2016 IEEE 13th International Conference on Signal Processing (ICSP) Pub Date : 2016-11-01 DOI: 10.1109/ICSP.2016.7877955
Gengrui Liang, Z. Shu, J. Jianguo
{"title":"Fusing deep convolutional network with SFM for 3D face reconstruction","authors":"Gengrui Liang, Z. Shu, J. Jianguo","doi":"10.1109/ICSP.2016.7877955","DOIUrl":"https://doi.org/10.1109/ICSP.2016.7877955","url":null,"abstract":"3D face reconstruction has long been a Research Focus and application hotsopt, in the field of 3D reconstruction from 2D face image sequences, the reconstruction result is impeded by the problems of the occlusion and illumination or pose variations frequently. Different from 3D morphable model fitting algorithm, the reconstruction method based on face feature points puts forward higher requirements to the robustness and accuracy. This paper propose a reconstruction method of fusing deep convolutional network for facial feature points extraction and factorization for SFM(Structure from Motion), we investigated the way of solving accurate sparse face structure matrix by importing a modified matrix, and the possibility of improving the realistic of 3D face reconstruction result by registering the sparse face structure and the general 3D face model. To reconstruct final dense face model, we use thin plate spline interpolation. The reconstruction result based on our method proved to be efficient and robust.","PeriodicalId":234499,"journal":{"name":"2016 IEEE 13th International Conference on Signal Processing (ICSP)","volume":"25 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126001511","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
Fast deblurring in video super resolution 在视频超分辨率快速去模糊
2016 IEEE 13th International Conference on Signal Processing (ICSP) Pub Date : 2016-11-01 DOI: 10.1109/ICSP.2016.7877909
Xueqing Yang, Tingting Fan
{"title":"Fast deblurring in video super resolution","authors":"Xueqing Yang, Tingting Fan","doi":"10.1109/ICSP.2016.7877909","DOIUrl":"https://doi.org/10.1109/ICSP.2016.7877909","url":null,"abstract":"Multi-frame super resolution has been well studied in recent years, but blur kernel is always assumed to be known in video super resolution problem. Most blind deconvolution algorithm can both estimate the blur kernel and the sharp image. In this paper, we originally adopt a fast single image blind deconvolution algorithm in video super resolution to estimate high-resolution image and blur kernel. In super resolution part, we use a Bayesian framework to estimate motion, noise parameters and high-resolution image simultaneously. In blind deconvolution part, we use the first reconstructed high-resolution image as blurred image to restore the sharp image and blur kernel, and smooth sparse prior is used here. By introducing blind deconvolution, super resolution algorithm only needs several iteration to reach promising results.","PeriodicalId":234499,"journal":{"name":"2016 IEEE 13th International Conference on Signal Processing (ICSP)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121736341","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 multi-objective optimal mobile robot path planning based on whale optimization algorithm 基于鲸鱼优化算法的多目标最优移动机器人路径规划
2016 IEEE 13th International Conference on Signal Processing (ICSP) Pub Date : 2016-11-01 DOI: 10.1109/ICSP.2016.7877851
Thi-Kien Dao, Tien-Szu Pan, Jeng-Shyang Pan
{"title":"A multi-objective optimal mobile robot path planning based on whale optimization algorithm","authors":"Thi-Kien Dao, Tien-Szu Pan, Jeng-Shyang Pan","doi":"10.1109/ICSP.2016.7877851","DOIUrl":"https://doi.org/10.1109/ICSP.2016.7877851","url":null,"abstract":"Due to the complex physical constraints in working space of robot, optimization for mobile robot operations satisfies not only one criterion but also several criteria. In this paper, a novel multi-objective method for optimal mobile robot path planning based on Whale optimization algorithm (WOA) is proposed. In the proposed method, two criteria of distance and smooth path of the robot path planning issue are transformed into a minimization one. The positions of the target and the obstacles in the environment are considered the fitness for the solution in WOA. The position of the globally best whale in each iteration is selected, and reached by the robot in sequence. In addition, the robot processor updates its information during the motion, and the environment is partially unknown for the robot due to the limit of the detection range of its sensors. Series of simulations are implemented in different static environments for the optimal path when the robot reaches its target. The results show that the proposed method provides the robot reaches its target with colliding free obstacles, and the proposed method may be the alternative method of optimization for robot planning.","PeriodicalId":234499,"journal":{"name":"2016 IEEE 13th International Conference on Signal Processing (ICSP)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115846593","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: 61
Single image super-resolution based on deep learning and gradient transformation 基于深度学习和梯度变换的单幅图像超分辨率
2016 IEEE 13th International Conference on Signal Processing (ICSP) Pub Date : 2016-11-01 DOI: 10.1109/ICSP.2016.7877915
Jingxu Chen, Xiaohai He, Honggang Chen, Qizhi Teng, L. Qing
{"title":"Single image super-resolution based on deep learning and gradient transformation","authors":"Jingxu Chen, Xiaohai He, Honggang Chen, Qizhi Teng, L. Qing","doi":"10.1109/ICSP.2016.7877915","DOIUrl":"https://doi.org/10.1109/ICSP.2016.7877915","url":null,"abstract":"In this paper, an effective single image super-resolution method based on deep learning and gradient transformation is proposed. Firstly, the low-resolution image is upscaled by convolutional neural network. Then we calculate the gradients of the upscaled image, and transform them into desired gradients by using gradient transformation network. The transformed gradients are utilized as a constraint to establish the reconstruction energy function. Finally, we optimize this energy function to estimate the high-resolution image. Experimental results show that our proposed algorithm can produce sharp high-resolution images with few ringing or jaggy artifacts, and our results have high values of the objective assessment parameters.","PeriodicalId":234499,"journal":{"name":"2016 IEEE 13th International Conference on Signal Processing (ICSP)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132407432","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
The method of phased array altimeter beamforming based on rotation platform 基于旋转平台的相控阵高度计波束形成方法
2016 IEEE 13th International Conference on Signal Processing (ICSP) Pub Date : 2016-11-01 DOI: 10.1109/ICSP.2016.7878105
He Tingting, Duan Rui, Huang Yong, Zhang Jiahao
{"title":"The method of phased array altimeter beamforming based on rotation platform","authors":"He Tingting, Duan Rui, Huang Yong, Zhang Jiahao","doi":"10.1109/ICSP.2016.7878105","DOIUrl":"https://doi.org/10.1109/ICSP.2016.7878105","url":null,"abstract":"In this paper, a phased array beamforming method based on the rotational platform is proposed. According to this method, the height of a platform can be measured accurately by adjusting the azimuth and elevation angles to keep the beam always point to the nadir point. Thus, the phased array altimeter needs to compensate the intersection change of the beam-point and the nadir point as a consequence of the platform translation and rotation. This paper deduces functions of angle error and phase compensation to calibrate the beam-point by establishing motion model of the platform, provides the method of weight calculating, and analyzes the update rate of weight. The curves illustrating the changes in directions of beam point as azimuth and elevation change respectively are provided by simulating. Finally, by means of simulation, making comparison between compensated and non-compensated antenna beam direction, we find the non-compensated beam is off nadir point with the changing motion of platform, while after compensating, the beam can be calibrated and pointed to the nadir again.","PeriodicalId":234499,"journal":{"name":"2016 IEEE 13th International Conference on Signal Processing (ICSP)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131561591","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
SAR image de-noising based on non-local similar block matching in NSST domain 基于NSST域非局部相似块匹配的SAR图像去噪
2016 IEEE 13th International Conference on Signal Processing (ICSP) Pub Date : 2016-11-01 DOI: 10.1109/ICSP.2016.7877947
Shaohai Hu, Xiaole Ma, Shuaiqi Liu, Dongsheng Yang
{"title":"SAR image de-noising based on non-local similar block matching in NSST domain","authors":"Shaohai Hu, Xiaole Ma, Shuaiqi Liu, Dongsheng Yang","doi":"10.1109/ICSP.2016.7877947","DOIUrl":"https://doi.org/10.1109/ICSP.2016.7877947","url":null,"abstract":"The traditional image de-noising in transform domain can get good de-noising effects, but it does not use the redundancy of the image information and the self-similarity of the image. In order to make full use of them and get better de-noising results, we propose a new SAR image de-noising method based on the non-local similar block matching in the non-subsampled shearlet domain. Firstly, we divide the image blocks into similar block groups with different characteristics by using the non-local similar block matching method; then, do the non-subsampled shearlet transform to every group and get the high and low frequency coefficients. Soft threshold is applied to the low frequency coefficients. Because the noise mainly exists in the high frequency component and the image coefficients in the transform domain have some correlation, we can define the adaptive threshold according to the correlation between the coefficients. Finally we can achieve the goal of the SAR image de-noising. The experimental results show that the proposed algorithm can keep more details about the original image and make less artificial texture. The proposed algorithm has stronger ability for image de-noising, and better visual effects.","PeriodicalId":234499,"journal":{"name":"2016 IEEE 13th International Conference on Signal Processing (ICSP)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131636158","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: 8
Image inpainting based on hidden Markov random field 基于隐马尔可夫随机场的图像绘制
2016 IEEE 13th International Conference on Signal Processing (ICSP) Pub Date : 2016-11-01 DOI: 10.1109/ICSP.2016.7877922
Hongxi Liu, Junxi Sun, Hongbin Sun, H. Lin
{"title":"Image inpainting based on hidden Markov random field","authors":"Hongxi Liu, Junxi Sun, Hongbin Sun, H. Lin","doi":"10.1109/ICSP.2016.7877922","DOIUrl":"https://doi.org/10.1109/ICSP.2016.7877922","url":null,"abstract":"In order to solve the problem of mismatching and structure disconnecting for exemplar-based image inpainting, we study the problem from the exemplar of known and unknown patches two part of the neighborhood, the introduction of the corresponding information consistency criteria from the matching patch and the unknown region to be repaired patch. Take full account of the degree of similarity to be repaired patches unknown information about the neighborhood and the matching patch. established hidden Markov random field image inpainting model, Be repaired area of the neighborhood be regarded as hidden random field, matching patches are determined by similarity and consistency, Effective solution to the mismatch of the exemplar inpainting method and structure of discontinuous problems, Experimental results show that our method is effective and practicable.","PeriodicalId":234499,"journal":{"name":"2016 IEEE 13th International Conference on Signal Processing (ICSP)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125201626","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 novel tensor completion based on APG for angle estimation in bistatic MIMO radar 一种基于APG的张量补全双基地MIMO雷达角度估计方法
2016 IEEE 13th International Conference on Signal Processing (ICSP) Pub Date : 2016-11-01 DOI: 10.1109/ICSP.2016.7877876
Donghui Xu, Haomiao Liu, Dongdong Yang, Hongguang Ma
{"title":"A novel tensor completion based on APG for angle estimation in bistatic MIMO radar","authors":"Donghui Xu, Haomiao Liu, Dongdong Yang, Hongguang Ma","doi":"10.1109/ICSP.2016.7877876","DOIUrl":"https://doi.org/10.1109/ICSP.2016.7877876","url":null,"abstract":"In this paper, a fast and stable tensor completion algorithm is proposed. The signal model of tensor completion based on truncated nuclear norm is given firstly. Then the truncated nuclear norm are utilized to solve object function. During the iterations, it proposes the adaptive accelerated proximal gradient algorithm, which also gives the method of renewing parameters. In the end, the effectiveness of proposed approach is verified by simulations.","PeriodicalId":234499,"journal":{"name":"2016 IEEE 13th International Conference on Signal Processing (ICSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133130138","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
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