The paper proposes Generalized False Discovery Rate (FDR) based thresholding procedure for estimating wavelet coefficients adaptively to compress ECG signal. To determine the adaptive threshold the connection between ...
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The paper proposes Generalized False Discovery Rate (FDR) based thresholding procedure for estimating wavelet coefficients adaptively to compress ECG signal. To determine the adaptive threshold the connection between thresholding and hypothesis testing is used. In the proposed algorithm False Discovery Threshold (FDT) is achieved by computing the probability of each detail coefficient. The computed probabilities are arranged in ascending order. The adaptive critical significance level is calculated by k-FWER and step up k-FDR procedures of multiple hypotheses testing. The significance levels are compared with computed probabilities to satisfy desired FDR, which provides the FDT. Finally two stage entropy coding is done using zero Run Length Encoding (RLE) followed by Huffman coding. As compared to existing techniques for ECG compression the proposed algorithms achieved very low average value of percentage root mean difference (PRD) at comparable compression ratios (CR). Very less PRD values signifies faithful reconstruction of original signal.
Bilateral Filter has properties of high noise removal. However, the estimating of suitable parameter by using an input image is required to obtain a fine denoising image. A method of parameter estimation using distrib...
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Bilateral Filter has properties of high noise removal. However, the estimating of suitable parameter by using an input image is required to obtain a fine denoising image. A method of parameter estimation using distribution distance has proposed. The method is optimal parameter estimation of bilateral filter based on distribution distance and assumption noise distribution that is estimated by differences between input and output images. However, there is problem if input images include many small edges. In this paper, we propose estimation of parameter using noise distribution that was estimated from estimation method that less susceptible to the original signal. Moreover, we show experimental results using proposed method.
Scheduling schemes provide efficient support of multimedia services in multi-user MIMO OFDM wireless *** cellular systems the base station transmits a signal intended for single user in a particular resource *** effic...
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Scheduling schemes provide efficient support of multimedia services in multi-user MIMO OFDM wireless *** cellular systems the base station transmits a signal intended for single user in a particular resource *** efficient utilization of available bandwidth in a system essential in modem wireless systems such as video streaming and voice over internet protocol(VoIP),which demands for higher data *** the user feedback the channel state information in the network,base station to schedule the more than one user data in a single resource *** properly utilizing the feedback information,scheduling algorithms are designed which select pairs of users which would maximize system *** this paper,We describe and compare the scheduling algorithms to improve the system capacity and fairness among the users proposed for the 3GPP Long term evolution(LTE) systems.
Recently, two methods for removing high density salt-and-pepper noise in images have been proposed by Esakkirajan et al. and Hong et al. However, their methods have not been yet compared experimentally. In this paper,...
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ISBN:
(纸本)9781479932115
Recently, two methods for removing high density salt-and-pepper noise in images have been proposed by Esakkirajan et al. and Hong et al. However, their methods have not been yet compared experimentally. In this paper, we compare them and show some experimental results. Additionally, we propose a hybrid method which is derived by combining the two methods, and experimentally show that the proposed method achieves higher values of both peak signal-to-noise ratio (PSNR) and image enhancement factor (IEF) than the two methods.
Time-of-Flight cameras based on the Photonic Mixer Device (PMD) emit modulated light and perform a correlation between the light signal reflected by the scene and a reference signal at the pixel level in order to esti...
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Time-of-Flight cameras based on the Photonic Mixer Device (PMD) emit modulated light and perform a correlation between the light signal reflected by the scene and a reference signal at the pixel level in order to estimate the difference of phase between the emitted and received signals. Well known issues of this technology are the low lateral resolution and the limited and scene-dependent depth accuracy. Superresolution algorithms have been proposed that combine several low resolution depth images to obtain an enhanced high resolution result, or make use of a higher resolution intensity image that can be registered with the depth image. To the best of our knowledge, methods in the related literature seem to ignore systematically the fact that the correlating pixels used for phase-based ToF imagers -e.g., PMD pixels- exhibit a complex structure that might lead to a non-trivial response function in spatial domain. This fact, which is irrelevant when working at pixel level due to the symmetry of pixel structure, becomes of capital importance when working at subpixel level. Ignoring it means assuming a wrong sensing model, which leads to false (or noisy) high resolution recovered images. The aim of this work is to characterize the response function of PMD pixels in spatial domain with micrometric resolution and gather novel and valuable information about the PMD sensing process within the pixel. The results of our experiments clearly confirm our hypothesis about a complex response function and give insights about the origins of noise. Additionally, we obtain a spatial characterization of the crosstalk.
Motion detection and segmentation of traffic vehicles in an outdoor environment, particularly under non ideal weather conditions, in the presence of camera noise and with variable or unfavorable luminance conditions i...
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Motion detection and segmentation of traffic vehicles in an outdoor environment, particularly under non ideal weather conditions, in the presence of camera noise and with variable or unfavorable luminance conditions is still an area of active research. Gaussian based background modeling is commonly used to detect moving objects in computer vision systems. However, it has some limitations it cannot effectively deal with sudden change in illumination, snowfall, fog, and repetitive motions such as swaying leaves. These nonideal outdoor conditions result in false motion detection. An alternative technique propose to detect and segment the moving vehicles by making use of dynamically adaptive threshold using the full-search sum of absolute difference (FSSAD) algorithm. Motion energy is obtained using sequence of frames that can be effectively be used to differentiate between moving vehicles and a dynamic background. Adaptive-motion threshold is used. It not only reduces the false motion but improves the computational efficiency as well.
based on poly-phase sampling and lookup table encryption techniques, a new image sharing scheme is presented with several aspects of innovations in this paper. Each shadow can be independently decrypted to obtain part...
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ISBN:
(纸本)9781479932115
based on poly-phase sampling and lookup table encryption techniques, a new image sharing scheme is presented with several aspects of innovations in this paper. Each shadow can be independently decrypted to obtain part of the original image, any pair of decrypted sub-images has very high correlation, it still obtains acceptable image quality when channel congestion occurs, and quality refinement of the recovered image is proportional to number of shadows obtained and achieves perfectly with all shadows. As a result, our method is highly suitable for internet applications in adverse environments with real-time progressive reconstruction. Experimental results demonstrate the promising characteristics of our method.
Foreign Object Debris (FOD) on airport runway is one of the greatest threats to aviation safety. The major characteristics of FOD are diversity and smallness. Synthetic aperture radar (SAR) has a natural advantage in ...
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Foreign Object Debris (FOD) on airport runway is one of the greatest threats to aviation safety. The major characteristics of FOD are diversity and smallness. Synthetic aperture radar (SAR) has a natural advantage in high resolution imaging, and is, therefore, very suitable for small and weak targets imaging on airport runway. Firstly, a new millimeter-wave FOD imaging system called Spotlight Circular Synthetic Aperture Radar (SC-SAR) is introduced in this paper. The SC-SAR system not only can solve the practical limitations for ground-based applications but also fully exploit the advantage of existing ground-based SAR systems for FOD imaging. Secondly, based on the geometry and imaging principle of SC-SAR, the adjusted version of the Range-Doppler imaging formula was presented. Finally, the simulation results validate feasibility of SC-SAR imaging system and algorithm.
According to target sparsity in observation scene, a novel scheme of microwave staring correlated imaging based on compressed sensing (MSCI-CS) is proposed with its established imaging model. As its imaging base and k...
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ISBN:
(纸本)9781479952212
According to target sparsity in observation scene, a novel scheme of microwave staring correlated imaging based on compressed sensing (MSCI-CS) is proposed with its established imaging model. As its imaging base and key element, the formation and specific meaning and characteristics of sensing matrix of temporal-spatial stochastic radiation fields (SM-TSSRF) are analyzed, while a new average cross-correlation function of SM-TSSRF is defined to represent its whole correlation characteristics, as well as the standard judgment condition of target reconstruction. The influence and restraint of radar parameters on SM-TSSRF are discussed emphatically, including emitted signal bandwidth, radar array scale, radar system configuration and its aperture etc. Finally, numerical simulations verify the correctness of theoretical analysis of SM-TSSRF and its potentiality of sparse sampling and high-resolution imaging.
Abnormal event detection has attracted a lot of attention in the computer vision research community during recent years due to the increased focus on automated surveillance systems to improve security in public places...
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Abnormal event detection has attracted a lot of attention in the computer vision research community during recent years due to the increased focus on automated surveillance systems to improve security in public places. Due to the scarcity of training data and the definition of an abnormality being dependent on context, abnormal event detection is generally formulated as a data-driven approach where activities are modeled in an unsupervised fashion during the training phase. In this work, we use a Gaussian mixture model (GMM) to cluster the activities during the training phase, and propose a Gaussian mixture model based Markov random field (GMM-MRF) to estimate the likelihood scores of new videos in the testing phase. Further-more, we propose two new features: optical acceleration, and the histogram of optical flow gradients; to detect the presence of any abnormal objects and speed violations in the scene. We show that our proposed method outperforms other state of the art abnormal event detection algorithms on publicly available UCSD dataset.
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