Coherent Line Removal: Filtering out harmonically related line interference from experimental data, with application to gravitational wave detectors

We describe a new technique for removing troublesome interference from external coherent signals present in the gravitational wave spectrum. The method works when the interference is present in many harmonics, as long as they remain coherent with one another. The method can remove interference even when the frequency changes. We apply the method to the data produced by the Glasgow laser interferometer in 1996 and the entire series of wide lines corresponding to the electricity supply frequency and its harmonics are removed, leaving the spectrum clean enough to detect possible signals previously masked by them. We also study the effects of the line removal on the statistics of the noise in the time domain. We find that this technique seems to reduce the level of non-Gaussian noise present in the interferometer and therefore, it can raise the sensitivity and duty cycle of the detectors.Comment: 14 pages, 8 figures, Revtex, psfig. To appear in Phys. Rev.

Weighted Repeated Median Smoothing and Filtering

We propose weighted repeated median filters and smoothers for robust non-parametric regression in general and for robust signal extraction from time series in particular. The proposed methods allow to remove outlying sequences and to preserve discontinuities (shifts) in the underlying regression function (the signal) in the presence of local linear trends. Suitable weighting of the observations according to their distances in the design space reduces the bias arising from non-linearities. It also allows to improve the efficiency of (unweighted) repeated median filters using larger bandwidths, keeping their properties for distinguishing between outlier sequences and long-term shifts. Robust smoothers based on weighted L1- regression are included for the reason of comparison. --Signal extraction ; Robust regression ; Outliers ; Breakdown point

A new family of non--linear filters for background subtraction of wide--field surveys

In this paper the definitions and the properties of a newle dedicated set of high-frequency filters based on smoothing-and-clipping are briefly described. New applications for reduction of wide--field 2048x2048 CCD spectral and direct images of a new deep survey KISS (KPNO International Spectral Survey) are also presented. The developed software is available both as a C subroutine and as an installed MIDAS environment command.Comment: 8 pages with 2 Postscript figures. The text with full figures obtainable from this http URL http://193.125.89.73/~akn/cont_with_figures.ps.g

A practical vision system for the detection of moving objects

The main goal of this thesis is to review and offer robust and efficient algorithms for the detection (or the segmentation) of foreground objects in indoor and outdoor scenes using colour image sequences captured by a stationary camera. For this purpose, the block diagram of a simple vision system is offered in Chapter 2. First this block diagram gives the idea of a precise order of blocks and their tasks, which should be performed to detect moving foreground objects. Second, a check mark () on the top right corner of a block indicates that this thesis contains a review of the most recent algorithms and/or some relevant research about it. In many computer vision applications, segmenting and extraction of moving objects in video sequences is an essential task. Background subtraction has been widely used for this purpose as the first step. In this work, a review of the efficiency of a number of important background subtraction and modelling algorithms, along with their major features, are presented. In addition, two background approaches are offered. The first approach is a Pixel-based technique whereas the second one works at object level. For each approach, three algorithms are presented. They are called Selective Update Using Non-Foreground Pixels of the Input Image , Selective Update Using Temporal Averaging and Selective Update Using Temporal Median , respectively in this thesis. The first approach has some deficiencies, which makes it incapable to produce a correct dynamic background. Three methods of the second approach use an invariant colour filter and a suitable motion tracking technique, which selectively exclude foreground objects (or blobs) from the background frames. The difference between the three algorithms of the second approach is in updating process of the background pixels. It is shown that the Selective Update Using Temporal Median method produces the correct background image for each input frame. Representing foreground regions using their boundaries is also an important task. Thus, an appropriate RLE contour tracing algorithm has been implemented for this purpose. However, after the thresholding process, the boundaries of foreground regions often have jagged appearances. Thus, foreground regions may not correctly be recognised reliably due to their corrupted boundaries. A very efficient boundary smoothing method based on the RLE data is proposed in Chapter 7. It just smoothes the external and internal boundaries of foreground objects and does not distort the silhouettes of foreground objects. As a result, it is very fast and does not blur the image. Finally, the goal of this thesis has been presenting simple, practical and efficient algorithms with little constraints which can run in real time