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Image Analysis and Signal Processing (IASP), 2011 International Conference on

Date 21-23 Oct. 2011

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Displaying Results 1 - 25 of 159
  • [Front and back cover]

    Page(s): c1 - c4
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    Freely Available from IEEE
  • [Title page]

    Page(s): i - ix
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  • Table of contents

    Page(s): x - xviii
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    Freely Available from IEEE
  • Selected mapping and partial transmit sequence schemes to reduce PAPR in OFDM systems

    Page(s): 1 - 5
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1087 KB) |  | HTML iconHTML  

    Orthogonal Frequency Division Multiplexing (OFDM) has been currently under intense research for broadband wireless transmission due to its robustness against multi-path fading. However, OFDM signals are characterized by large peak-to-average power ratios (PAPR), which can reduce the system efficiency. To overcome this problem, in this paper, based on the definition of the PAPR in OFDM systems, we will mainly investigate the PAPR reduction performance with two different PAPR reduction methods: the selective mapping (SLM) and partial transmit sequence (PTS). A comprehensive analysis and comparison are conducted in terms of all possible influencing factors and PAPR reduction performance, respectively. Some research findings are obtained based on the simulation results. The results verify that PTS method provides a better PAPR reduction performance compared to SLM method and the probability of high PAPR with increasing the number of sub-blocks in PTS technique decreases obviously, compared to the original OFDM signal. In addition, SLM algorithm is more suitable if the system can tolerate more redundant information; otherwise, PTS algorithm is more acceptable when complexity becomes the first considering factor. View full abstract»

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  • A novel method for frame rate up-conversion

    Page(s): 6 - 9
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (881 KB) |  | HTML iconHTML  

    In this paper, we proposed a new motion compensated interpolation (MCI) algorithm for frame rate up-conversion (FRUC) in multimedia applications. First, we propose the bilateral motion estimation (ME) scheme to obtain the motion field of an interpolated frame without yielding the hole and overlapping problems. Secondly, we partition the block which the sum of bilateral absolute differences (SBAD) is bigger than a threshold into four sub-blocks and re-estimate by bilateral ME. Thirdly, we smoothed the motion vectors (MVs) using spatio-temporal motion vector smoothing (MVS). Finally, we use the overlapped block motion compensation to generate interpolated frames and further reduce block artifacts. Experimental results show that the proposed algorithm provides a better image quality than conventional methods both objectively and subjectively. View full abstract»

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  • A fast algorithm for discrete sine transform using first-order moment

    Page(s): 10 - 15
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1029 KB) |  | HTML iconHTML  

    A fast algorithm for discrete sine transform (DST) is proposed. Through derivation the traditional DST is transformed into the computation of a first-order moment, which can be implemented by a simple parallel structure without multiplications. The comparison with some existing methods on the computation and the hardware complexity shows the advantage of our method under certain conditions. The approach is also applicable to other discrete sine transforms. View full abstract»

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  • Hooke and jeeves algorithm for linear least-square problems in sparse signal reconstruction

    Page(s): 16 - 20
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1284 KB) |  | HTML iconHTML  

    Greedy algorithms are the major algorithmic approaches to sparse signal reconstruction from an incomplete set of linear measurements. All the greedy algorithms involve solving linear least-square problems. This is usually implemented via CGLS. Though CGLS uses a fixed number of iterations, experiments confirm that CGLS costs more than 50 percent of the total running time of greedy algorithms. In order to reduce the running time, we introduce a method called HJLS, which applies Hooke and Jeeves algorithm to solve the least-square problems. As the columns of the measurement matrix are nearly orthogonal, HJLS also converges in a fixed number of iterations. Comparative experiments between HJLS and CGLS show that the number of iterations used in HJLS is fewer and implementing HJLS instead of CGLS reduces the total running time of greedy algorithms by more than 20 percent. View full abstract»

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  • Low SNR signal time-frequency analyzing method

    Page(s): 21 - 25
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1651 KB) |  | HTML iconHTML  

    Signal time-frequency analysis under low signal-to-noise ratio (SNR) conditions is an important part of signal processing. As Wigner-Ville distribution (WVD) transformation can save all the traits of the original signal in the special space where the frequency is zero, a new method is proposed to extract the signal time-frequency relationship under low SNR conditions and to estimate the extent to improve the SNR after the denoising processing. Through signal time-frequency extracting comparison and parameter extracting comparison, it is proved that this method has higher extraction validity and feasibility. View full abstract»

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  • Research on Lhasa Tibetan prosodic model of journalese based on respiratory signal

    Page(s): 26 - 30
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (901 KB) |  | HTML iconHTML  

    In accordance with the actual development for Tibetan speech synthesis, the paper has taken news text as training corpora, analyzed the speech and prosodic features of Tibetan Lhasa dialect and confirmed the respiratory signal parameters with prosodic features. It has confirmed 6 classes of 39 dimensions context feature parameters in terms of previous prosodic structure analysis results. It uses RBF neural network to establish prosodic model and output 10 dimensions prosodic control parameters, and testing to know the predictable nature of the established model. View full abstract»

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  • On Comparison Of Pilot-Aided OFDM channel estimation algorithms

    Page(s): 31 - 35
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (964 KB) |  | HTML iconHTML  

    Orthogonal Frequency Division Multiplexing (OFDM) is an attractive modulation technique for communication between unmanned underwater vehicles (UUV) and a distant mother platform. The objective of this study is improving channel estimation accuracy in OFDM system because channel state information is required for signal detection at the receiver and its accuracy affects the overall performance of the system and it is essential to improve the channel estimation for more reliable communications. In this paper, the pilot signal estimation based on Least Square (LS), together with channel interpolation based on the discrete cosine transform, namely DCT-based LS estimator, is compared with LS channel estimation approaches and discussed. Two well known performance criteria: Mean Square Error (MSE) and Bit Error Rate (BER) are used for comparison by using Monte Carlo Simulations for 16 quartered amplitude modulation (16QAM). The results verify that the DCT-based LS estimator has a better performance for OFDM systems. Moreover, the effect of power limitation in terms of SNR and the number of pilots for a wireless channel is determined to compare the DCT-based LS estimator. The result indicates that the estimator with large number of pilots has better performance, but increases the computational complexity. View full abstract»

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  • Echo energy analysis for pulse position modulation sequences used for non-crosstalk sonar systems

    Page(s): 36 - 41
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1095 KB) |  | HTML iconHTML  

    High echo energy is important in sonar systems to increase measurement range. A sufficient condition is derived and obtained to achieve high echo energy for pulse position modulation excitation sequences. This paper addresses echo energy analysis under the premise that crosstalk between different sonar transducers can be avoided. Experiments validate the derived sufficient condition. View full abstract»

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  • Dual-ADC based digital calibration of timing skew for a time-interleaved ADC

    Page(s): 42 - 45
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (824 KB) |  | HTML iconHTML  

    The performance of time-interleaved analog-to-digital converters (TIADCs) is seriously restricted by the mismatch of the timing skew between ADC channels. The concept of dual-ADC based calibration is that setting two ADC to sample the same input signal synchronously, and the differences of the two outputs are used in calibration algorithm to estimate and compensate the errors in each ADC. Based on this method, we propose a novel 7-channel TIADC with digital background calibration, which focuses on calibrating the timing skew of each ADC channel. The calibration algorithm is based on the least-mean-square iteration. Simulation of the designed 14-bit 7-channel TIADC with MATLAB shows that, with ± 0.02Ts timing skew, and normalized input frequency fin/fs=0.05, signal to noise and distortion ratio and spurious free dynamic range of the output signal of the TIADC after calibration reach 85.9dBc and 103dBc, and improve 28dBc and 43dBc, respectively, compared to the uncalibrated output signal. View full abstract»

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  • A family Particle Swarm Optimization based on the family tree

    Page(s): 46 - 51
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1002 KB) |  | HTML iconHTML  

    The concept of the family was previously introduced into Particle Swarm Optimization (PSO). To further study the multi-group structure of the Family PSO (FPSO), this paper introduces the family tree into the FPSO. It made different families form a family tree and a swarm consisted of some family trees. In the experiment, topological distance was used to form a family and three spatial structures of the family trees were simply defined and demonstrated in two-dimensional space. Simulations for seven benchmark functions demonstrated that two family trees in a swarm and each family had 2 particles that performed better than other combinations. Results also showed the multi-group structure of FPSO was a problem deserving of study at high-dimensional space. View full abstract»

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  • Stability analysis of FAST TCP using PI transfer function

    Page(s): 52 - 55
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (830 KB) |  | HTML iconHTML  

    A new approach for the stability analysis of FAST TCP system is used for the investigation of one special kind of dynamical systems. This approach is based on results from the stability theory, optimal control theory, and variational methods. The optimal control approach allows us to obtain sufficient algebraic stability conditions for FAST TCP system. The way to obtain necessary and sufficient conditions for stability of systems with parameter r is shown in this paper. This method leads, in some cases, to algebraic necessity and sufficient conditions of absolute stability. Furthermore, case results illustrate the validity of parameter r for the stability of FAST TCP. View full abstract»

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  • Research on E-government information service mechanism based on unified communication technology

    Page(s): 56 - 61
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (401 KB) |  | HTML iconHTML  

    Unified communication can provide flexible service for e-government, and also, can achieve more efficient government business collaboration with low-cost. In this paper, we discuss the government information service mechanism based on unified communication technology that integrates voice, data, and video services, and so on. View full abstract»

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  • 3-D geometric signal compression method based on compressed sensing

    Page(s): 62 - 66
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1123 KB) |  | HTML iconHTML  

    This paper provides a compression method of three-dimensional meshes based on compressed sensing. First, this method gets the 3-D geometric signal through discrete representing the three-dimensional meshes. Then, we construct a basis using Laplace operator of the three-dimensional meshes. Thus, we get the sparse representation of the 3-D geometric signal based on this basis. Last, we complete compressing the three-dimensional meshes, through random sampling geometry signals based on compressed sensing. In the recovery process, we reconstruct the 3-D geometric signal through optimizing 1-norm of the sparse signal. This method completed the compression of three-dimensional meshes in the sampling process. Experimental results show that the compression ratio of this method is high, the restore effect is good and it is suitable for large-scale data compression. View full abstract»

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  • The research on arabic numeral symbol's use in poster design

    Page(s): 67 - 70
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (9682 KB) |  | HTML iconHTML  

    This article presents the origin and development of Arabic numbers, the effect and the culture differences in graphic spread. We analyze the Arabic numeral symbols in graphic originality, and draw out the development space of the Arabic numeral symbols in shape and meaning of poster design. As a kind of mathematical symbols without national boundary, the Arabic numeral symbols have a large space in poster design. View full abstract»

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  • An algorithm based on HRRP for target recognition

    Page(s): 71 - 73
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (526 KB) |  | HTML iconHTML  

    Based on the scattering center model, the dissertation makes detailed analysis on the physical property of HRRP samples and points out the HRRP sensitivity of target-aspect. The average HRRP for feature extraction is presented in a small target-aspect after the HRRP preprocessing methods are discussed, and experiment results based on the SVM classifier are given to show the efficiency of the proposed method. View full abstract»

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  • The prefix and suffix query of Chinese word segmentation algorithm for maximum matching

    Page(s): 74 - 77
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (177 KB) |  | HTML iconHTML  

    Chinese word segmentation is a key technology for automatic summarization. Whether the segmentation is successful and has no ambiguity or not will directly affect sentence weight calculation. In the segmentation process, the structure of word segmentation dictionary is particularly important. A rational structure of a word segmentation dictionary can improve the segmentation process of the dictionary query speed, and, thus, improves the efficiency of Chinese word segmentation. This paper is based on the dictionary of Hash structure. In this paper, the authors adopt the prefix and suffix query approach to build word segmentation dictionary, combined with an improved Chinese word segmentation algorithm for maximum matching to improve the segmentation efficiency and accuracy. View full abstract»

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  • Skin color and feature-based face detection in complicated backgrounds

    Page(s): 78 - 83
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4734 KB) |  | HTML iconHTML  

    An efficient face detection scheme that can detect multiple faces in a color image with a complex environment and different illumination levels is proposed in this paper. The first stage adopts skin color-based segmentation to search potential face regions. The second stage detects the lip in potential face regions using a lip color model and searches the eyes using geometry textures. The last stage clips the face region using an optimization ellipse. Results of the study demonstrate that the proposed approach performs well in detecting various poses in different illumination conditions and complicated backgrounds. View full abstract»

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  • Blurring length estimation using ringing artifacts in a deblurred image

    Page(s): 84 - 88
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (5531 KB) |  | HTML iconHTML  

    The restoration quality of a motion-blurred image is highly dependent on the estimation accuracy of the motion blurring parameter. This manuscript presents a novel and precise method for estimation of the motion blurring length, wherein the ringing artifact amount of a deblurred image is measured by energy proportion contained in appropriate frequency bands, and a blurring length with minimum ringing artifact amount is taken as the optimal estimation of the true blurring length. Experimental results show good performance of the proposed algorithm in motion blurring length estimation. View full abstract»

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  • Ball Carrier Detection and Behavior Recognition in Basketball Match Using Covariance Descriptor

    Page(s): 89 - 93
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1912 KB) |  | HTML iconHTML  

    This paper presents a novel approach for ball carrier detection and behavior recognition in a basketball match. Considering the cluttered background, fast motion of the players and the low resolution of the player images in the basketball match video, a covariance descriptor is adopted to fuse multiple visual features of the player, which can be characterized as a point on the Riemannian manifold and can be projected to the tangent space through the homeomorphic mapping. Therefore, detection and behavior recognition of the ball carrier is simultaneously completed on the tangent space through the trained multiclass LogitBoost. Experimental results demonstrate that the proposed method performs well on video recorded in the NBA basketball matches. View full abstract»

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  • Fast bilateral filtering using image redundancy reduction

    Page(s): 94 - 97
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1839 KB) |  | HTML iconHTML  

    A bilateral filter is an edge-preserving filter that is widely applied in the image processing field in spite of its length of computation time and space complexity. In this paper, we propose a fast filtering method using image redundancy reduction; our approach can reduce the filtering computation time by reducing the redundant operations between adjacent blocks of pixels. We also apply this approach to bilateral filtering, which can then run faster, and does not require additional space consumption. View full abstract»

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  • NMS-based blurred image sub-pixel registration

    Page(s): 98 - 101
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (686 KB) |  | HTML iconHTML  

    Sub-pixel accurate registration is the challenging aspect of super-resolution reconstruction. However, the blur contained in the low-resolution images will result in inaccurate registration and an unsatisfactory reconstruction result. Therefore, this paper introduces a blurred image sub-pixel registration method based on Non-Maxima Suppression (NMS). By analyzing the relationship between the image edge energy and the registration precision, NMS technology is used to extract the local gradient magnitude maximum point set adaptively, which is used for image registration as strong information. Experimental results show that this method can improve the registration accuracy of blur low-resolution images. View full abstract»

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  • Sea-surface image super-resolution based on sparse representation

    Page(s): 102 - 107
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (895 KB) |  | HTML iconHTML  

    Learning-based super-resolution (SR) is a popular SR technique that uses application-specific priors to recover missing high-frequency components in low resolution (LR) images. In this paper, we propose a novel approach for obtaining high-resolution (HR) image with solely a single low-resolution input sea-surface image. It is based on sparse representation via dictionary learning. As the image patch can be well represented through a sparse linear combination of elements from the training over-complete dictionary, this paper proposes a two-step statistical approach integrating the global model and a local patch model. During the training process, we divide the corresponding training images into patches and take the schismatic hierarchical clustering algorithm to get the idiosyncratic patches aimed at the background of sea-surface, using the jointly training method generating two over-complete dictionaries for the LR and HR images. In the reconstructed process, we infer the HR patch for each LR patch by the sparse prior in the local model, and recover the HR image via the reconstruction constraint in the global model. For our particular applications of sea-surface image SR, the proposed method has a more effective performance than other SR algorithms. View full abstract»

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