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About 4,071 papers for “wavelet-based estimation”

Wavelet based estimation on cell confluence

Amalka Pinidiyaarachchi, Hans Claesson, Crolina Wählby · 2009

Light microscopes are essential research tools in biology and medicine. Cell and tissue staining methods have improved immensely over the years and microscopes are now equipped with digital image acquisition capabilities. The image data produced require development of specialized analysis methods. This thesis presents digital image analysis methods for cell image data in 2D, 3D and time sequences.Stem cells have the capability to differentiate into specific cell types. The mechanism behind differentiation can be studied by tracking cells over time. This thesis presents a combined segmentation and tracking algorithm for time sequence images of neural stem cells.The method handles splitting and merging of cells and the results are similar to those achieved by manual tracking.Methods for detecting and localizing signals from fluorescence stained biomolecules are essential when studying how they function and interact. A study of Smad proteins, that serve as transcription factors by forming complexes and enter the cell nucleus, is included in the thesis. Confocal microscopy images of cell nuclei are delineated using gradient information, and Smad complexes are localized using a novel method for 3D signal detection. Thus, the localization of Smad complexes in relation to the nuclear membrane can be analyzed. A detailed comparison between the proposed and previous methods for detection of point-source signals is presented, showing that the proposed method has better resolving power and is more robust to noise.In this thesis, it is also shown how cell confluence can be measured by classification of wavelet based texture features. Monitoring cell confluence is valuable for optimization of cell culture parameters and cell harvest. The results obtained agree with visual observations and provide an efficient approach to monitor cell confluence and detect necrosis.Quantitative measurements on cells are important in both cytology and histology. The color provided by Pap (Papanicolaou) staining increases the available image information. The thesis explores different color spaces of Pap smear images from thyroid nodules, with the aim of finding the representation that maximizes detection of malignancies using color information in addition to quantitative morphological parameters.The presented methods provide useful tools for cell image analysis, but they can of course also be used for other image analysis applications.

Cited by 0

3D Wavelet-Based Optical Flow Estimation

Mutaz. AbdulWahab · Engineering and Technology Journal · 2007

In this paper, a new algorithm for accurate optical flow estimation using discretewavelet approximation is proposed. The image sequences are always assumed tobe noiseless in the computation of optical flow, since there is always a method thatcan perform such task. One of the main application areas of the wavelettransform is that of noise reduction in images. The basic technique is to transformthe noisy input image into a domain, in which the main signal energy isconcentrated into as few coefficients as possible, while the noise energy isdistributed more uniformly over all coefficients. The choice of the transform isrepresent an important tool in optical flow estimation. In this paper, severalalgorithms of 1-D, 2-D and 3-D wavelet transforms are adapted for the estimationof optical flow for the first time.

Cited by 0Open access

IF Estimation based on Wavelet Transform

Yanjie Zhang, V. Prinet · 2004

For InSAR processing, the precision of the interferometric phase is the key problem for all kinds of its applications. While it is badly affected by many decorrelation factors such as thermal noise, atmospheric effect, the imaging geometry, the different Doppler Centroid, the processing and so on, all of them add the difficulty to do phase-unwrapping. Nowadays phase-unwrapping based on Instantaneous Frequency (IF) estimation has gained more attention [9][10]. IF can not only be used to do phase-unwrapping, but also can be used to do the interferogram filtering. How to estimate the unbiased IF from a low SNR interferogram is very important and challenging. Here the multi-scale analysis advantage of the WT is used to estimate IF. From the theory of WT, the IF of a signal can be extracted from the ridges of its WT. Beside, the WT can be an efficient tool to analyze multi-component signals. In this work the Morlet wavelet is used. 1.

Cited by 0

Wavelet-based Estimation of Generalized Fractional Process

Akira Kawanaka, Alex Gonzaga · Methods of Information in Medicine · 2007

The proposed method is relatively computationally and statistically efficient. It allows for estimation of the long-memory parameter without knowledge of the short-memory parameters. Moreover it provides a more general model of biomedical signals that exhibit periodic long-range dependence, such as ECG data, whose relatively unobtrusive recording may be advantageous in assessing or predicting some physiological or pathological conditions from the estimated values of the parameters.

Cited by 9

Routing with Wavelet-Based Self-Similarity Estimation

César Vargas Rosales, Luis J. Manzanero · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2004

The discovery of self-similar behavior in data traffic has initiated strong research in the area of traffic modeling. However, the way it affects the routing process is a subject not yet studied. This work presents the idea of providing intelligence to routers by estimating the Hurst Parameter using wavelets in a data link and uses this value as part of the routing metric. The motivation is to keep packets from using paths with high values of the Hurst Parameter, since in those paths the traffic tends to be bursty and therefore being more probable to drop packets and increase delay due to congestion. The algorithm is implemented for the Open Shortest Path First (OSPF) routing protocol in a simulation environment. Numerical results show that this technique is useful to provide traffic with low values of end-to-end delay and with smaller variance than those obtained when using traditional routing protocols.

Cited by 0

AR spectrum estimation based on wavelet representation

F.G.V. Resende, Keiichi Tokuda, M. Kaneko · 2002

A new adaptive AR spectrum estimation method is proposed. The cost function is defined by using the discrete-time wavelet transform coefficients of the linear prediction error. Instead of a single window throughout the whole frequency spectrum, a wavelet-like windowing method is used to increase the frequency resolution of the low-frequency components and to improve the time resolution of the high-frequency components. Special properties of the covariance matrix are used to derive an RLS algorithm which requires O(M/sup 2/) operations. Simulation results show that the wavelet based spectrum estimation method gives fine frequency resolution at low frequencies and good time resolution at high frequencies, while with conventional methods it is possible to have only one of these characteristics.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Cited by 5

An Efficient Wavelet-Based Motion Estimation Algorithm

Jongwoo Bae · IEICE Transactions on Information and Systems · 2005

In this paper, we propose a wavelet-based fast motion estimation algorithm for video sequence encoding with a low bit-rate. By using one of the properties of the wavelet transform, multi-resolution analysis (MRA), and the spatial interpolation of an image, we can simultaneously reduce the prediction error and the computational complexity inherent in video sequence encoding. In addition, by defining a significant block (SB) based on the differential information of the wavelet coefficients between successive frames, the proposed algorithm enables us to make up for the increase in the number of motion vectors when the MRME algorithm is used. As a result, we are not only able to improve the peak signal-to-noise ratio (PSNR), but also reduce the computational complexity by up to 67%.

Cited by 6

Globally Optimal Wavelet-Based Motion Estimation using

Interscale Edge And, Onur G. Guleryuz · 2004

We propose a non-iterative, globally optimal dense motion field estimation technique based on a multiresolutional probability model. We consider the field to be estimated in terms of its wavelet coe#cients and carry out the estimation in the field&amp;apos;s wavelet transform domain. Our approach models interscale dependencies of the wavelet coe#cients and allows for smooth, edge, and occluded regions in the field. We obtain segmentations of the field and our results show that the field estimates yield accurate depictions of scene motion. The globally optimal nature of our estimation framework allows it to be applicable in scenes exhibiting large motion and in settings of ill-posed motion. Hence, our algorithms can also be used to determine accurate initializations for optical flow type estimation techniques, which use more sophisticated models but can only obtain locally optimal solutions that are heavily dependent on initial conditions. The performance is illustrated on several examples.

Cited by 0

Routing with Wavelet-Based Self-Similarity Estimation

Vargas Rosales, César, Manzanero, Luis J. · Redalyc (Universidad Autónoma del Estado de México) · 2004

"The discovery of self-similar behavior in data traffic has initiated strong research in the area of traffic modeling. However, the way it affects the routing process is a subject not yet studied. This work presents the idea of providing intelligence to routers by estimating the Hurst Parameter using wavelets in a data link and uses this value as part of the routing metric. The motivation is to keep packets from using paths with high values of the Hurst Parameter, since in those paths the traffic tends to be bursty and therefore being more probable to drop packets and increase delay due to congestion. The algorithm is implemented for the Open Shortest Path First (OSPF) routing protocol in a simulation environment. Numerical results show that this technique is useful to provide traffic with low values of end-to-end delay and with smaller variance than those obtained when using traditional routing protocols."

Cited by 0

Gabor Wavelet Based Pose Estimation For Face

Recognition Gkberk Akarun, B. Gökberk, L. Akarun et al. · 2001

One of the major difficulties in face recognition systems is the in-depth pose variation problem. Most face recognition approaches assume that the pose of the face is known. In this work, we use a variation of Gabor wavelet transform for the representation of human face images to efficiently solve the pose estimation problem. Parameters of the Gabor wavelets, namely frequency and orientation, are adjusted to gain better performance. Principal Component Analysis is performed to reduce the dimensionality without a significant loss in the performance. Our results show that Gabor wavelet based filtering of images improves the performance of the pose estimation module.

Cited by 0

Model selection for wavelet-based signal estimation

Vladimir Cherkassky, Xuhui Shao · 2002

There has been a growing interest in wavelet-based methods for signal estimation from noisy samples. We compare popular wavelet thresholding methods with model selection using VC generalization bounds developed for finite samples. Since wavelet methods are linear (in parameters), the VC-dimension of linear models can be accurately estimated. Successful application of VC-theory to wavelet denoising also requires specification of a suitable structure on a set of wavelet basis functions. We propose such a structure suitable for orthogonal basis functions, which includes wavelets as a special case. The combination of the proposed structure with VC bounds yields a new powerful method for signal estimation with wavelets. Our comparisons indicate that using VC bounds for model selection gives uniformly better results than other wavelet thresholding methods under small sample/high noise setting. On the other hand, with large samples model selection becomes trivial, and most reasonable methods (including wavelet thresholding heuristics) perform reasonably well.

Cited by 13

Wavelet Based Estimation Of A Semi Parametric

Generalized Linear Model, François G. Meyer · 2000

This work provides a new approach to estimate the parameters of a semi-parametric generalized linear model in the wavelet domain. The method is illustrated with the problem of detecting significant changes in fMRI signals that are correlated to a stimulus time course. The fMRI signal is described as the sum of two effects : a smooth trend and the response to the stimulus. The trend belongs to a subspace spanned by large scale wavelets. We have developed a scale space regression that permits to carry out the regression in the wavelet domain while omitting the scales that are contaminated by the trend. Experiments with fMRI data demonstrate that our approach can infer and remove drifts that cannot be adequately represented with low degree polynomials. Our approach results in a noticeable improvement by reducing the false positive rate and increasing the true positive rate.

Cited by 0