We develop a sequential wavelet domain and temporal filtering scheme, with jointly optimized parameters, which results in high-quality video denoising over a large range of noise levels. In this scheme, spatial filtering is performed by a spatially adaptive Bayesian wavelet shrinkage in a redundant wavelet representation. In the next filtering stage, a motion detector controls selective, recurs...

In this article, we are concerned with tracking an object of interest in video stream. We propose an algorithm that is robust against occlusion, the presence of confusing colors, abrupt changes in the object feature space and changes in object size. We develop the algorithm within a Bayesian modeling framework. The state space model is used for capturing the temporal correlation in the sequence...

An attempt to analyse formant movements within the cycle of vocal fold vibration by linear prediction is presented. To achieve a high temporal resolution the duration of the analysis window is adjusted shorter than the fundamental period. The measurement noise increased thereby is counteracted by averaging the parameter estimates by clustering. Preprocessing by a linear band pass filter and by ...

In the study of noise from propellers and ducted fans, rigorous signal decomposition into harmonic and broadband components is essential for the development of high-fidelity predictive models. Current spectral methods and phase averaging techniques lack the temporal resolution to compensate for fluctuations in operating condition intrinsic to real world experiments. In this paper we use a Vold-...

In this paper we introduce a novel adaptive beamformer which also copes with incoherent background noise. After derivation of the optimum filter based on a weighted time-domain least-squares error criterion we present an efficient realization by applying a multichannel frequency-domain algorithm exhibiting RLS-like convergence. For the computation of this algorithm a simultaneous estimation of ...

When compiling climatological means of air temperature, station data usually are selected on the basis of whether they exist within a fixed base period (e.g. 1961 to 1990). Within such analyses, station records that do not contain sufficient data during the base period or only contain data from other base periods are excluded. If between-station variability is of interest (e.g. a map or gridded...

424  Abstract—Image denoising is one of the fundamental problems in image processing. In this paper, a novel approach to suppress noise from the image is conducted by applying the interquartile range (IQR) which is one of the statistical methods used to detect outlier effect from a dataset. A window of size kk was implemented to support IQR filter. Each pixel outside the IQR range of the kk ...

The electrocardiogram (ECG) is widely used for diagnosis of heart diseases. Good quality ECG signals are utilized by physicians for interpretation and identification of physiological and pathological phenomena. Several techniques have been proposed to extract the ECG components contaminated with the background noise and allow the measurement of subtle features in the ECG signal. One of the comm...

Introduction: Time-resolved phase contrast (PC) MRI is important for many clinical applications and requires fast data acquisition. In order to increase spatiotemporal resolution or reduce total acquisition times, parallel imaging techniques such as kt-SENSE, kt-BLAST [1] and kt-Grappa [2] have been introduced. For kt-BLAST/ kt-SENSE it has been shown that high reduction factors of the order of...

In this paper, we present a method that we call on-surface convolution which extends the classical notion of a 2D digital filter to the case of digital surfaces (following the cuberille model). We also define an averaging mask with local support which, when applied with the iterated convolution operator, behaves like an averaging with large support. The interesting property of the latter averag...