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2014 19th International Conference on Digital Signal Processing最新文献

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Spatial-temporal depth de-noising for Kinect based on texture edge-assisted depth classification 基于纹理边缘辅助深度分类的Kinect时空深度去噪
2014 19th International Conference on Digital Signal Processing Pub Date : 2014-09-18 DOI: 10.1109/ICDSP.2014.6900681
Yatong Xu, Xin Jin, Qionghai Dai
{"title":"Spatial-temporal depth de-noising for Kinect based on texture edge-assisted depth classification","authors":"Yatong Xu, Xin Jin, Qionghai Dai","doi":"10.1109/ICDSP.2014.6900681","DOIUrl":"https://doi.org/10.1109/ICDSP.2014.6900681","url":null,"abstract":"The emergence of Kinect facilitates the real-time and low-cost depth capture. However, the quality of its depth map is still inadequate for further applications due to holes, noises and artifacts existing within its depth information. In this paper, a Kinect depth de-noising algorithm is proposed to enhance the stability and reliability of Kinect depth map by exploiting spatial-temporal depth classification beside edges. Depth edges are realigned by extracted texture edges. Spatial and temporal depth classification is retrieved and exploited adaptively to remove the blurs around the edges. Experimental results demonstrate that the proposed algorithm provides much sharper and clearer edges for the Kinect depth. Compared with the original depth and the depths refined by existing approaches, the spatial-temporal de-noised depth information provided by the proposed approach enhances the quality of some advanced processing e.g. 3D reconstruction prospectively.","PeriodicalId":301856,"journal":{"name":"2014 19th International Conference on Digital Signal Processing","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127945434","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
Dynamic scene rain removal for moving cameras 动态场景雨移除移动摄像机
2014 19th International Conference on Digital Signal Processing Pub Date : 2014-09-18 DOI: 10.1109/ICDSP.2014.6900689
Cheen-Hau Tan, Jie Chen, Lap-Pui Chau
{"title":"Dynamic scene rain removal for moving cameras","authors":"Cheen-Hau Tan, Jie Chen, Lap-Pui Chau","doi":"10.1109/ICDSP.2014.6900689","DOIUrl":"https://doi.org/10.1109/ICDSP.2014.6900689","url":null,"abstract":"Rain removal is important to ensure the robustness of applications which rely on video input towards rainy conditions. A number of algorithms have thus been proposed to remove the rain effect based on the properties of rain. However, most of these methods are not able to remove rain effectively for scenes taken from moving cameras. We propose a rain removal algorithm which can effectively remove rain from dynamic scenes taken from moving cameras by improving a recent state-of-the-art rain removal method. We do so by first aligning neighboring frames to a target frame before the target frame is de-rained. Experiments show that our proposed method is able to remove rain effectively for moving camera scenes.","PeriodicalId":301856,"journal":{"name":"2014 19th International Conference on Digital Signal Processing","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125771521","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
A new efficient dictionary and its implementation on retinal images 一种新的高效词典及其在视网膜图像上的实现
2014 19th International Conference on Digital Signal Processing Pub Date : 2014-09-18 DOI: 10.1109/ICDSP.2014.6900785
D. Thapa, K. Raahemifar, V. Lakshminarayanan
{"title":"A new efficient dictionary and its implementation on retinal images","authors":"D. Thapa, K. Raahemifar, V. Lakshminarayanan","doi":"10.1109/ICDSP.2014.6900785","DOIUrl":"https://doi.org/10.1109/ICDSP.2014.6900785","url":null,"abstract":"Sparse representation of signals and images using an over-complete basis function (dictionary) has attracted a lot of attention in the literature recently. Atoms of a dictionary are either chosen from a predefined set of functions (e.g. Sine, Cosine or Wavelets), or learned from a training set (KSVD). Recently, a nonlinear (NL) dictionary has been proposed by adding NL functions, such as polynomials, rational, logarithmic, exponential, and phase shifted and higher order cosine functions to the conventional Discrete Cosine Transform (DCT) atoms. In this paper, we present a comprehensive performance comparison of various NL functions that are added to the DCT dictionary. The NL dictionary is also compared with the other known dictionaries such as DCT, Haar and KSVD-based learned dictionary for sparse image reconstruction. In the second part, the NL dictionary is exploited for sparsity based image denoising. Retinal images are used for the analysis.","PeriodicalId":301856,"journal":{"name":"2014 19th International Conference on Digital Signal Processing","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126668696","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
Multistatic radar imaging via decentralized and collaborative subspace pursuit 基于分散协同子空间追踪的多基地雷达成像
2014 19th International Conference on Digital Signal Processing Pub Date : 2014-09-18 DOI: 10.1109/ICDSP.2014.6900756
Gang Li, P. Varshney, Yimin D. Zhang
{"title":"Multistatic radar imaging via decentralized and collaborative subspace pursuit","authors":"Gang Li, P. Varshney, Yimin D. Zhang","doi":"10.1109/ICDSP.2014.6900756","DOIUrl":"https://doi.org/10.1109/ICDSP.2014.6900756","url":null,"abstract":"The task of multistatic radar imaging can be converted to the problem of jointly sparse signal recovery. In this paper, the algorithm named decentralized and collaborative subspace pursuit (DCSP) is utilized in multistatic radar systems to obtain a high-resolution image. By embedding collaboration among radar nodes and fusion strategy into each iteration of the standard subspace pursuit (SP) algorithm, DCSP is capable of providing satisfactory image even if some radar nodes suffer from relatively low signal-to-noise ratios (SNRs). Compared to the existing algorithms based on linear programming, DCSP has much lower computational complexity at the cost of increased communication overhead in the radar network.","PeriodicalId":301856,"journal":{"name":"2014 19th International Conference on Digital Signal Processing","volume":"98-B 10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128477422","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
Blind separation of sufficiently sparse sources in multichannel compressed sensing 多通道压缩感知中充分稀疏源的盲分离
2014 19th International Conference on Digital Signal Processing Pub Date : 2014-09-18 DOI: 10.1109/ICDSP.2014.6900719
Hongwei Xu, Ning Fu, Congru Yin, Liyan Qiao, Xiyuan Peng
{"title":"Blind separation of sufficiently sparse sources in multichannel compressed sensing","authors":"Hongwei Xu, Ning Fu, Congru Yin, Liyan Qiao, Xiyuan Peng","doi":"10.1109/ICDSP.2014.6900719","DOIUrl":"https://doi.org/10.1109/ICDSP.2014.6900719","url":null,"abstract":"Conventional approaches for blind source separation (BSS) are almost based on the Nyquist sampling theory. Recently, compressed sensing (CS) theory is applied to BSS for the fact that the information of a signal can be preserved in a relatively small number of linear projections. The traditional method for compressive BSS mainly involves two steps: recovering mixed signals from compressed observations and separating source signals from the recovered mixed signals. This paper presents a novel framework for separating and reconstructing the sufficiently sparse sources from compressively sensed linear mixtures simultaneously. Compared with the traditional compressive BSS, the proposed approach can reduce the requirements of sampling speed and operating rate of the devices. Moreover, our approach has better reconstruction results. Simulation results demonstrate the proposed algorithm can separate multichannel sufficiently sparse sources successfully.","PeriodicalId":301856,"journal":{"name":"2014 19th International Conference on Digital Signal Processing","volume":"186 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124316582","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
Parallelizing sparse recovery algorithms: A stochastic approach 并行稀疏恢复算法:一种随机方法
2014 19th International Conference on Digital Signal Processing Pub Date : 2014-09-18 DOI: 10.1109/ICDSP.2014.6900814
A. Shah, A. Majumdar
{"title":"Parallelizing sparse recovery algorithms: A stochastic approach","authors":"A. Shah, A. Majumdar","doi":"10.1109/ICDSP.2014.6900814","DOIUrl":"https://doi.org/10.1109/ICDSP.2014.6900814","url":null,"abstract":"This work proposes a novel technique for accelerating sparse recovery algorithms on multi-core shared memory architectures. All prior works attempt to speed-up algorithms by leveraging the speed-ups in matrix-vector products offered by the GPU. A major limitation of these studies is that in most signal processing applications, the operators are not available as explicit matrices but as implicit fast operators. In such a practical scenario, the prior techniques fail to speed up the sparse recovery algorithms. Our work is based on the principles of stochastic gradient descent. The main sequential bottleneck of sparse recovery methods is a gradient descent step. Instead of computing the full gradient, we compute multiple stochastic gradients in parallel cores; the full gradient is estimated by averaging these stochastic gradients. The other step of sparse recovery algorithms is a shrinkage operation which is inherently parallel. Our proposed method has been compared with existing sequential algorithms. We find that our method is as accurate as the sequential version but is significantly faster - the larger the size of the problem, the faster is our method.","PeriodicalId":301856,"journal":{"name":"2014 19th International Conference on Digital Signal Processing","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121654128","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
A patch-number and bandwidth adaptive non-local kernel regression algorithm for multiview image denoising 一种用于多视点图像去噪的补丁数和带宽自适应非局部核回归算法
2014 19th International Conference on Digital Signal Processing Pub Date : 2014-09-18 DOI: 10.1109/ICDSP.2014.6900676
J. F. Wu, Chong Wang, Z. C. Lin, S. Chan
{"title":"A patch-number and bandwidth adaptive non-local kernel regression algorithm for multiview image denoising","authors":"J. F. Wu, Chong Wang, Z. C. Lin, S. Chan","doi":"10.1109/ICDSP.2014.6900676","DOIUrl":"https://doi.org/10.1109/ICDSP.2014.6900676","url":null,"abstract":"This paper presents an automatic patch number selection method for bandwidth adaptive non-local kernel regression (BA-NLKR) algorithm, which was recently proposed for improving the performance of conventional non-local kernel regression (NLKR) in image processing. Although BA-NLKR addressed the important issue of bandwidth selection, the number of non-local patches, which impacts the integration of local and non-local information, however is chosen empirically. In this paper, we propose a new algorithm for automatic patch number selection based on the intersecting confidence intervals (ICI) rule in order to achieve better performance. Moreover, the proposed patch number and bandwidth adaptive NLKR (PBA-NLKR) is applied to the denoising problem of multiview images. The effectiveness of the proposed algorithm is illustrated by experimental results on denoising for both single-view and multi-view images.","PeriodicalId":301856,"journal":{"name":"2014 19th International Conference on Digital Signal Processing","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125656251","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
Sparse coding based lip texture representation for visual speaker identification 基于唇纹稀疏编码的视觉说话人识别
2014 19th International Conference on Digital Signal Processing Pub Date : 2014-09-18 DOI: 10.1109/ICDSP.2014.6900736
Jun-Yao Lai, Shilin Wang, Xing-Jian Shi, Alan Wee-Chung Liew
{"title":"Sparse coding based lip texture representation for visual speaker identification","authors":"Jun-Yao Lai, Shilin Wang, Xing-Jian Shi, Alan Wee-Chung Liew","doi":"10.1109/ICDSP.2014.6900736","DOIUrl":"https://doi.org/10.1109/ICDSP.2014.6900736","url":null,"abstract":"Recent research has shown that the speaker's lip shape and movement contain rich identity-related information and can be adopted for speaker identification and authentication. Among all the static lip features, the lip texture (intensity variation inside the outer lip contour) is of high discriminative power to differentiate various speakers. However, the existing lip texture feature representations cannot describe the texture information adequately and provide unsatisfactory identification results. In this paper, a sparse representation of the lip texture is proposed and a corresponding visual speaker identification scheme is presented. In the training stage, a sparse dictionary is built based on the texture samples for each speaker. In the testing stage, for any lip image investigated, the lip texture information is extracted and the reconstruction errors using all the dictionaries for every speaker are calculated. The lip image is identified to the speaker with the minimum reconstruction error. The experimental results show that the proposed sparse coding based scheme can achieve much better identification accuracy (91.37% for isolate image and 98.21% for image sequence) compared with several state-of-the-art methods when considering the lip texture information only.","PeriodicalId":301856,"journal":{"name":"2014 19th International Conference on Digital Signal Processing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134250583","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
Presence detection of long-and-short-code DS-SS signals using the phase linearity of multichannel sensors 利用多通道传感器的相位线性度检测长、短码DS-SS信号
2014 19th International Conference on Digital Signal Processing Pub Date : 2014-09-18 DOI: 10.1109/ICDSP.2014.6900677
Can Uysal, T. Filik
{"title":"Presence detection of long-and-short-code DS-SS signals using the phase linearity of multichannel sensors","authors":"Can Uysal, T. Filik","doi":"10.1109/ICDSP.2014.6900677","DOIUrl":"https://doi.org/10.1109/ICDSP.2014.6900677","url":null,"abstract":"In this study, the detection of direct sequence spread spectrum (DS-SS) signals in white Gaussian noise without prior knowledge is investigated for spatially distributed multichannel wideband sensor array. A novel technique for the presence detection of both the long-and-short-code DS-SS signals is proposed which uses the frequency domain spatial covariance matrix of the sensor array. The technique is based on the linearity of the phase response of the wideband spatial covariances of cross sensors along the bandwidth of the signal. It is shown in simulations that the technique can detect DS-SS signals in a stable way at low signal to noise ratio (SNR) without any prior information and assumption on target. In addition, the proposed method can detect DS-SS signals in the presence of narrow band interference and multipath reflections.","PeriodicalId":301856,"journal":{"name":"2014 19th International Conference on Digital Signal Processing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131919217","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
Stereo confidence metrics using the costs of surrounding pixels 使用周围像素成本的立体置信度度量
2014 19th International Conference on Digital Signal Processing Pub Date : 2014-09-18 DOI: 10.1109/ICDSP.2014.6900808
Sanghun Kim, D. Yoo, Young Hwan Kim
{"title":"Stereo confidence metrics using the costs of surrounding pixels","authors":"Sanghun Kim, D. Yoo, Young Hwan Kim","doi":"10.1109/ICDSP.2014.6900808","DOIUrl":"https://doi.org/10.1109/ICDSP.2014.6900808","url":null,"abstract":"In this paper, we propose two new stereo confidence metrics which are used for estimating the reliability of a stereo matching result more accurately. Unlike the conventional metrics which exploit the cost information of the pixel being processed only, the proposed metrics utilize the cost information of the surrounding pixels as well as the pixel being processed. By checking whether the costs of the surrounding pixels at the target disparity are the local minimum or not, or calculating the ratio between costs of surrounding pixels, the proposed metrics can estimate the reliability of a stereo matching result more correctly. Experimental results show that the two proposed metrics improve the area under the curve of the error rate as a function of disparity map density by up to 0.012 and 0.025, compared to the existing methods, respectively.","PeriodicalId":301856,"journal":{"name":"2014 19th International Conference on Digital Signal Processing","volume":"2006 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127662504","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: 5
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