P. W. Verbeek, H. A. Vrooman, and L. J. van Vliet. Low-level image processing by max-min filters. Signal Processing, 15(3):249--258, October 1988. 48  Home/Search   Document Not in Database   Summary   Related Articles   Check

....high frequency noise, this technique is not suitable in our application because important high frequencies that characterise the up take speed of the contrast tracer would also be heavily damped. Morphological operators, on the other hand, retain the large edges. The morphological minmax filter [43], which we used for preprocessing, is defined as: 2 ) max min ) min max = I y I y w I y y filter b b b b (37) with b(t) t (w 1) 2, t (w 1) 2 and I(t) denoting the intensity associated with voxel I(x,t) Generally, the strength of signals obtained from an ....

P.W. Verbeek, H.A. Vrooman, L.J.v. Vliet, Low-level image-processing by max min filters, Signal Processing 15 (3) (1988) 249-258.

....not be very accurate (still the maximum of the lowest intensity peak might give a reasonable estimate) In these cases an approach based on mathematical morphology or fitting of a polynomial might work. In the first approach an opening operation can be used to estimate the shape of the background [20]. The second approach fits a low order polynomial through the pixels [21] The accuracy and the bias of the fit will be improved if the fit is done through background pixels only. Therefore the image needs to be segmented (coarsely) in object and background pixels. One way of doing this is to use ....

P. W. Verbeek, H. A. Vrooman, and L. J. v. Vliet, "Low-level image processing by max-min filters," Signal Processing, vol. 15, pp. 249-258, 1988.

....could hamper the image recognition procedure. The most important of these is the non uniform brightness of the image of the reference plate, due to vignetting and illumination effects. This is done by computing an upper envelope to the measured intensities in the image (see e.g. Verbeek et al. [5]) and dividing the image by this upper envelope. In the resulting image, the body of the reference plate appears uniformly bright, and the black markers will be much darker, though not quite uniformly black. By carefully choosing a number of contour levels and tracing these contours in the ....

P.W. Verbeek, H.A. Vrooman, L.J. van Vliet, Low-level Image Processing by Max-Min Filters, Signal Processing 15 (1988) p. 249-258.

....(comparisons per sample) of the proposed algorithm is very close to log 2 n, where n is the size of the given window. A flexible hardware implementation for n ranging between two consecutive powers of two is discussed. 1 Introduction Max min filters are widely used in signal image processing [2] [4]. Let fx i ; i = 0; Ng be a sequence of samples. The problem of running max min filtering within a window of size n is to determine a sequence fy i g, where y i is either the maximum or the minimum of n consecutive samples, x i ; x i 1 ; x i n Gamma1 . The computational complexity ....

P. W. Verbeek, H. A. Vrooman, L.J. Vliet, "Low-Level Image Processing by Max-Min Filters", Signal Processing, vol. 15, no. 3, pp. 249-258, Oct. 1988.

....06, GREECE Tel: 30 31 996304, Fax: 30 31 996304, email: pitas zeus.csd.auth.gr Dinu Coltuc is with the Research Institute for Electrical Engineering, P.O. BOX 16 296, Bucharest, ROMANIA 1 Introduction Max min filters are widely used in nonlinear signal and image processing applications [1] [4]. They are very attractive, since their computation requires only comparisons and no arithmetic operations. The computational complexity of max min filters (i.e. the number of comparisons per sample) depends on the size of the filter window. A direct evaluation of the computational complexity may ....

P. W. Verbeek, H. A. Vrooman, L.J. Vliet, "Low-Level Image Processing by Max-Min Filters", Signal Processing, vol. 15, no. 3, pp. 249-258, Oct. 1988.

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Verbeek, P.W., H.A. Vrooman, and L.J. Van Vliet, Low-Level Image Processing by Max-Min Filters. Signal Processing, 1988. 15: p. 249-258.

....round Gauss trunc 345 [ Optimized FFT Unifo, m square [ Recursire Gauss Fig. 5, Ratio of computation times of various filter algorithms to the fastest implementation the recurslye Gaussian as a function of a. square and circular) use an incremental updating process for improved speed [13]. The FFT implementation uses a real FFT and look up tables for the sine and cosine values. The overall results are shown in Fig. 5. For all values of a 1.0, the recursive algorithm is the fastest. At a = 5.0, for example, the Gaussian FIR convolutions are 3.3 and 5.3 times slower when the ....

P.W. Verbeek, H.A. Vrooman and L.J. Van Vliet, "Lowlevel image processing by max min filters", Signal Processin (, Vol. 15, No. 3, October 1988, pp. 249-258.

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P. W. Verbeek, H. A. Vrooman, and L. J. van Vliet. Low-level image processing by max-min filters. Signal Processing, 15(3):249--258, October 1988. 48

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P.W. Verbeek, H.A. Vrooman, L.J. van Vliet, Low-level Image Processing by Max-Min Filters, Signal Processing 15 (1988)p. 249-258.

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P.W. Verbeek, H.A. Vrooman, L.J. van Vliet, Low-level Image Processing by Max-Min Filters, Signal Processing 15 (1988) p. 249-258.

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P.W. Verbeek, H.A. Vrooman, L.J. van Vliet, Low-level Image Processing by Max-Min Filters, Signal Processing 15 (1988) p. 249-258.

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