1,721,110 research outputs found
Bias-free adaptive IIR filtering
No full textWe present a new family of algorithms that solve the bias problem in the equation-error based adaptive infinite impulse response (IIR) filtering. A novel constraint, called the constant-norm constraint, unifies the quadratic constraint and the monic one. By imposing the monic constraint on the mean square error (MSE) optimization, the merits of both constraints are inherited and the shortcomings are overcome. A new cost function based on the constant-norm constraint and Lagrange multiplier is defined. Minimizing the cost function gives birth to a new family of bias-free adaptive IIR filtering algorithms. For example, two efficient algorithms belonging to the family are proposed. The analysis of the stationary points is presented to show that the proposed methods can indeed produce bias-free parameter estimates in the presence of white noise. The simulation results demonstrate that the proposed methods indeed produce unbiased parameter estimation, while being simple both in computation and implementation.open113sciescopu
SAR image enhancement based on phase-extension inverse filtering
No full textIn this paper we present a new post enhancement method for single look complex (SLC) SAR imagery, which is based on phase-extension inverse filtering. To obtain a high-quality SAR image, the proposed method improves the mainlobe resolution as well as efficiently suppresses the sidelobes with low computational complexity. The proposed method extends the effective signal band up to the maximum-bandwidth allowed by a SAR system. The band-extension is achieved by adjusting the magnitude level of matched filtered SAR spectrum. Because the proposed method preserves the phase components of the spectrum unlike other super-resolution techniques and deconvolution techniques, it enhances a SAR image without causing any displacement. To verify the efficacy of the proposed method we apply it to a simulated SAR image and a real ERS-1 SAR image. The result images show that the proposed method improves the mainlobe resolution with low sidelobe levels.open112sciescopu
Unbiased equation-error adaptive IIR filtering based on monic normalization
No full textWe present a novel way to remove the bias in equation-error based adaptive infinite impulse response (IIR) filtering by conceiving a scheme called monic normalization. It is found that normalizing all the coefficients of the denominator filter by the first coefficient after each adaptation removes the bias and leads to unbiased estimates. The analysis of stationary points is presented to show that the proposed method can indeed produce unbiased parameter estimates in the presence of noise. The computer simulation results also demonstrate that the proposed method performs better than or comparable to existing algorithms, while requiring much lower computational complexity.X1131sciescopu
Image contrast enhancement based on the generalized histogram
No full textWe present an adaptive contrast enhancement method based on the generalized histogram, which is obtained by relaxing the restriction of using the integer count For each pixel, the integer count I allocated to a pixel is split into the fractional count and the remainder count. The generalized histogram is generated by accumulating the fractional count for each intensity level and distributing the remainder count uniformly throughout the intensity levels. The intensity mapping function, which determines the contrast gain for each intensity level, is derived from the generalized histogram. Since only the fractional part of the count allocated to each pixel is used for increasing the contrast gain of its intensity level, the amount of contrast enhancement is adjusted by varying the fractional count according to regional characteristics. The proposed scheme produces visually more pleasing results than the conventional histogram equalization. (c) 2007 SPIE and IS&T.open11620sciescopu
Pyramid-structured progressive image transmission using quantisation error delivery in transform domains
No full textThe authors propose a pyramid-structured progressive image transmission scheme in which quantisation error delivery is applied to the transform coefficients of the images represented by the pyramid. Quantisation error delivery makes it possible to reprocess at the lower level the information lost at each level of the pyramid. This is one important method for achieving lossless reproduction of an original image in pyramid-structured progressive image transmission. When the images represented by the pyramid are compressed by the transform and the quantisation is applied to the transform coefficients, however, the existing approach in the literature requires the inverse transform of the quantisation error, which is a computational overhead. To remove this drawback, the authors propose a new method to accomplish quantisation error delivery directly in the transform domain. Using the proposed method, the quantisation error at the transform coefficient of each level can be delivered and Incorporated in the transform coefficient of the lower level. The simulation results show that the proposed method also has excellent coding performance for the intermediate levels of the pyramid.X1111sciescopu
A hierarchical block matching algorithm using selective elimination of candidate motion vectors
No full textIn this paper, a new hierarchical block matching algorithm using mean and difference pyramids is presented. The detection of motion vectors at each level of the pyramid is accomplished by selectively eliminating the candidate motion vectors that cannot provide the best match at the next lower level. The remaining motion vectors at each level are propagated and used as the initial motion vectors at the next lower level. Therefore, the possibility of falling into local minima can be significantly reduced. The simulation results show that the proposed method has excellent performance with reduced computational complexity.open11sciescopu
An affine projection adaptive filtering algorithm with selective regressors
No full textWe present a novel affine projection algorithm which reduces complexity by selecting a subset of input regressors at every iteration. The optimal selection of input regressors is derived by comparing the cost functions based on the principle of minimum disturbance. The proposed algorithm shows good convergence performance with various experimental results.X1133sciescopu
Adaptive IIR filtering with combined regressor and combined error
No full textThe adaptive IIR filtering is known to be the more efficient method for system identification compared with the adaptive FIR filtering but is not widely used because of the bias and stability problems of the conventional adaptive IIR filtering algorithms. This paper presents a new algorithm called the CRCE (combined regressor and combined error) algorithm that can overcome the problems of the conventional algorithms by using the combined form of the regression vector and the estimation error. By controlling the composition of the combined regressor and the combined error, the CRCE algorithm continuously adjusts the coefficient update equation to achieve convergence stability and estimation accuracy. The computer simulation results also demonstrate that the performance of the proposed algorithm is better than those of the conventional algorithms. (C) 1997 Elsevier Science B.V.X116sciescopu
A Complementary Pair LMS algorithm for adaptive filtering
No full textThis paper presents a new algorithm that can solve the problem of selecting appropriate update step size in the LMS algorithm. The proposed algorithm, called a Complementary Pail LMS (CP-LIMS) algorithm, consists of two adaptive filters with different update step sizes operating in parallel, one filter re-initializing the other with the better coefficient estimates whenever possible. This new algorithm provides the faster convergence speed and the smaller steady-state error than those of a single filter with a fixed or variable step size.open1114sciescopu
Error concealment for MPEG-2 video decoders with enhanced coding mode estimation
No full textWe present a novel error-concealment method for MPEG-2 video decoders. Imperfect transmission of block-based compressed images may result in loss of blocks, making image degradation inevitable. In the hybrid error-concealment method, both spatial and temporal error concealment repair the damaged regions through adaptive interpolation in the respective domains. In order for the hybrid method to yield good performance it should be presumed that coding-mode estimation is correct. In reality, however erroneous coding mode estimation frequently occurs, ultimately resulting in poor performance. In the proposed method, we reduce the number of erroneously estimated coding-modes by utilizing the fact that MPEG-2 video coding is based on block-based coding. This enhanced hybrid technique effectively conceals the lost blocks by raising the probability of correct coding mode estimation by exploiting the image characteristics such as scene changes and complex motions. Through computer simulations on damaged images we show that the proposed method has excellent performance.X115sciescopu
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