{"title":"Sep of cooperative systems using Amplify and Forward or Decode and Forward relaying","authors":"S. Amara, H. Boujemaa, N. Hamdi","doi":"10.5281/ZENODO.41673","DOIUrl":"https://doi.org/10.5281/ZENODO.41673","url":null,"abstract":"In this paper, we derive the Symbol Error Probability (SEP) of cooperative systems using Amplify and Forward (AF) or Decode and Forward (DF) relaying. In AF relaying, each relay amplifies and retransmits to the destination the received signal from source. The destination combines the signals received from all relays and the source using aMaximum Ratio Combining (MRC) strategy. For DF relaying, each relay decodes the received signal. It forwards the decoded symbol if it decodes correctly. Otherwise, it remains idle. In DF relaying, two protocols are presented. In the first one, each relay decodes only the received signal from the source. In the second one, each relay combines the signals received from the source and the previous m relays. Exact and asymptotic SEP of AF and DF relaying are derived and compared to simulation results.","PeriodicalId":106989,"journal":{"name":"2009 17th European Signal Processing Conference","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122252991","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}
B. Penna, T. Tillo, Marco Grangetto, E. Magli, G. Olmo
{"title":"A technique for blood detection in wireless capsule endoscopy images","authors":"B. Penna, T. Tillo, Marco Grangetto, E. Magli, G. Olmo","doi":"10.5281/ZENODO.41479","DOIUrl":"https://doi.org/10.5281/ZENODO.41479","url":null,"abstract":"Wireless capsule endoscopy is an innovative technology for visualizing anomalies in the gastrointestinal tract, useful to replace traditional endoscopic diagnosis. Its advantages are related to the capability to reach the duodenum and small intestine, while eliminating the discomfort of patients. The time spent by a physician analyzing the results of wireless capsule endoscopy video can vary between 45 and 180 minutes, limiting its widespread diffusion. Therefore, methods able to perform an automatic pre-screening of images of interest are necessary. This paper presents an innovative technique to detect bleeding regions in wireless capsule endoscopy video. Experimental results show that the proposed algorithm exhibits a low false alarm rate, and is effective at reducing the time needed to analyze video sequences.","PeriodicalId":106989,"journal":{"name":"2009 17th European Signal Processing Conference","volume":"229 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122909512","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}
{"title":"Maximum likelihood range estimation for 3D-imaging based on pseudo-noise optical modulation","authors":"M'hamed-Ali El Mechat, Hans-Andrea Loeliger","doi":"10.5281/ZENODO.41568","DOIUrl":"https://doi.org/10.5281/ZENODO.41568","url":null,"abstract":"Acquiring real-time 3D images poses many challenges. Many 3D-imaging systems are based on estimating the time-of-flight (TOF) of photons between an emitter and a receiver, which in turn is based on transmitting a pseudo-noise optical signal and correlation measurements. The precision of such measurements is limited by photon shot noise. In this paper, we develop a maximum-likelihood estimator for the TOF (and thus for the range) that takes into account the Poisson distribution of the detected photons. The proposed estimator is shown to give better range estimates than a standard estimator that is used in current systems. The improvement is particularly significant when the period of the pseudo-noise sequence-based modulation signal is short.","PeriodicalId":106989,"journal":{"name":"2009 17th European Signal Processing Conference","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122425405","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}
{"title":"Data processing and pattern recognition in high-throughput capillary electrophoresis","authors":"Gerardo Ceballos, J. Paredes, L. Hernández","doi":"10.5281/ZENODO.41595","DOIUrl":"https://doi.org/10.5281/ZENODO.41595","url":null,"abstract":"A specific method for massive Capillary Electrophoresis data analysis based on pattern recognition techniques in the wavelet domain is presented. Low-resolution, denoised electropherograms are obtained by applying several pre-processing algorithms including discrete wavelet transform, denoising, detection of region of interest and baseline correction. The resultant signal is mapped into multi-character sequences exploiting the first derivative information and multi-level peak height quantization. Next, local alignment algorithms are applied on the coded sequence for peak pattern recognition. Finally, Gaussian approximation is performed to assure precise peak-height measurements.","PeriodicalId":106989,"journal":{"name":"2009 17th European Signal Processing Conference","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121391696","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}
{"title":"Multiscale kernel smoothing using a lifting scheme","authors":"M. Jansen, C. Damerval","doi":"10.5281/ZENODO.41389","DOIUrl":"https://doi.org/10.5281/ZENODO.41389","url":null,"abstract":"This paper discusses the idea of a lifting scheme for multiscale implementation of kernel estimation procedures used in statistical estimation. The resulting decomposition is related to the Burt-Adelson pyramid, but the design of the filters is well adapted to nonequispaced samples. The proposed decomposition has an oversampling rate of 2, where the oversampling can be seen as an alternative to primal lifting steps (update steps) as a tool for stabilising and anti-aliasing. We then propose an adaptive version of this multiscale kernel estimation with truncated kernels. Truncated kernels allow sharp representations of jumps. Illustrations show that our method is numerically well conditioned, suffers less from visual effects due to false detections, and allows indeed sharp transitions if equiped with an adaptive choice among truncated kernels. All variants of the proposed method have linear computational complexity.","PeriodicalId":106989,"journal":{"name":"2009 17th European Signal Processing Conference","volume":"57 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128635208","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}
{"title":"Merged inverse quantization and IDCT for optimized decoder implementation","authors":"Jin Li, M. Gabbouj, J. Takala, Hexin Chen","doi":"10.5281/ZENODO.41284","DOIUrl":"https://doi.org/10.5281/ZENODO.41284","url":null,"abstract":"This paper proposes an efficient technique to reduce the complexity of implementation for inverse discrete cosine transform (IDCT)-based video decoders. The proposed method merges the inverse quantization and IDCT into a single procedure, which is referred to as inverse quantized IDCT (IQIDCT), such that the decoded coefficients do not need to be inverse quantized prior to the inverse transform. Thus, the computations related to inverse quantization are omitted. Since the cosine transform basis can be constructed before decoding, the proposed IQIDCT effectively replaces the need for computing power with little additional memory. The performance of the proposed algorithm is evaluated by comparing it with the original XVID decoder which uses the traditional separate inverse quantization and IDCT method. Experiments show the efficiency of the proposed method in reducing the overall decoding complexity. Moreover, it does not result in any video quality degradation. The proposed method is particularly suitable for low-power processors in multimedia systems.","PeriodicalId":106989,"journal":{"name":"2009 17th European Signal Processing Conference","volume":"41 24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128494624","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}
{"title":"Simplifying Gaussian mixture models via entropic quantization","authors":"F. Nielsen, Vincent Garcia, R. Nock","doi":"10.5281/ZENODO.41383","DOIUrl":"https://doi.org/10.5281/ZENODO.41383","url":null,"abstract":"Mixture models are a crucial statistical modeling tool at the heart of many challenging applications in computer vision, machine learning, and text classification among others. In this paper, we describe a novel and efficient algorithm for simplifying Gaussian mixture models using a generalization of the celebrated k-means quantization algorithm tailored to relative entropy in statistical distribution spaces. Our algorithm extends easily to arbitrary mixture of exponential families. The proposed method is shown to compare favourably well with the state-of-the-art unscented transform clustering algorithm both in terms of time and quality performances.","PeriodicalId":106989,"journal":{"name":"2009 17th European Signal Processing Conference","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129249728","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}
{"title":"Posterior Cramer-Rao lower bound for mobile tracking in mixed LOS/NLOS conditions","authors":"Liang Chen, Lenan Wu, R. Piché","doi":"10.5281/ZENODO.41606","DOIUrl":"https://doi.org/10.5281/ZENODO.41606","url":null,"abstract":"The paper studies the theoretical error lower bound of the mobile tracking problem in mixed Line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. A new method is presented to compute the posterior Cramer-Rao lower bound (CRLB): the mobile state is first estimated by decentralized EKF method, then sigma point set and unscented transformation are applied to calculate Fisher information matrix (FIM). Numerical results show that the error performance of three algorithms is in a good agreement with the theoretical bounds.","PeriodicalId":106989,"journal":{"name":"2009 17th European Signal Processing Conference","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115453927","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}
{"title":"A new robust estimation method for short-term load forecasting","authors":"Y. Chakhchoukh","doi":"10.5281/ZENODO.41646","DOIUrl":"https://doi.org/10.5281/ZENODO.41646","url":null,"abstract":"This paper presents a new robust method to estimate the parameters of ARIMA models. This method makes use of the minimum Hellinger distance estimator (MHDE) together with a robust filter cleaner able to reject a large fraction of outliers, and a Gaussian maximum likelihood estimation which handles missing values. The main advantages of the procedure are its easiness, robustness, high efficiency and practical execution. Its effectiveness is demonstrated on Monte Carlo simulations and an example of the forecasting of the French daily electricity consumptions.","PeriodicalId":106989,"journal":{"name":"2009 17th European Signal Processing Conference","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114515378","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}
{"title":"Texture classification using wavelet-domain BDIP and BVLC features","authors":"H. So, Mi Hye Kim, N. Kim","doi":"10.5281/ZENODO.41780","DOIUrl":"https://doi.org/10.5281/ZENODO.41780","url":null,"abstract":"In this paper, we propose a texture classification method using local texture features BDIP (block difference of inverse probabilities) and BVLC (block variation of local correlation coefficients) in wavelet domain. BDIP and BVLC are known to be good texture features which are bounded and well normalized to reduce the effect of illumination and catch the own properties of textures effectively. In the method, a target image is first decomposed into wavelet subbands. BDIPs and BVLCs are then computed in wavelet subbands. The means and standard deviations of subband BDIPs and BVLCs and the subband standard deviations are fused into a texture feature vector. Finally, the Bayesian distance between the feature vector of a query image and that of each class is stably measured and it is classified into the class of minimum distance. Experimental results for three test databases (DBs) show the proposed method yields excellent performances.","PeriodicalId":106989,"journal":{"name":"2009 17th European Signal Processing Conference","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127085334","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}