Zayed M . Ramadan - Academia.edu (original) (raw)
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Papers by Zayed M . Ramadan
Adaptive Filtering Primer With Matlab®
... Zayed M. Ramadan received his BS and MS degrees in electrical engineer-ing (EE) from Jordan U... more ... Zayed M. Ramadan received his BS and MS degrees in electrical engineer-ing (EE) from Jordan University of Science and Technology in ... signal processing 5 2.1 Discrete-time signals 5 2.2 Transform-domain representation of discrete-time signals 5 2.3 The Z-Transform 11 2.4 ...
TELKOMNIKA (Telecommunication Computing Electronics and Control)
In this paper, the effect of the kernel size of Wiener and Gaussian filters on their image restor... more In this paper, the effect of the kernel size of Wiener and Gaussian filters on their image restoration qualities has been studied and analyzed. Four sizes of such kernels, namely 3x3, 5x5, 7x7 and 9x9 were simulated. Two different types of noise with zero mean and several variances have been used: Gaussian noise and speckle noise. Several image quality measuring indices have been applied in the computer simulations. In particular, mean absolute error (MAE), mean square error (MSE) and structural similarity (SSIM) index were used. Many images were tested in the simulations; however the results of three of them are shown in this paper. The results show that the Gaussian filter has a superior performance over the Wiener filter for all values of Gaussian and speckle noise variances mainly as it uses the smallest kernel size. To obtain a similar performance in Wiener filtering, a larger kernel size is required which produces much more blur in the output mage. The Wiener filter shows poor performance using the smallest kernel size (3x3) while the Gaussian filter shows the best results in such case. With the Gaussian filter being used, similar results of those obtained with low noise could be obtained in the case of high noise variance but with a higher kernel size.
American Journal of Engineering and Applied Sciences
American Journal of Signal Processing, 2014
This paper introduces a new variable step-size LMS algorithm in which the step-size is dependent ... more This paper introduces a new variable step-size LMS algorithm in which the step-size is dependent on both data and error normalization. With an appropriate choice of the value of the fixed step-size and the ratio between error and data normalization in the proposed algorithm, a trade-off between speed of convergence and misadjustment can be achieved. The performance of the algorithm
Southeastern Symposium on System Theory, 2004
This paper introduces a new variable step size LMS algorithm in which the step size varies invers... more This paper introduces a new variable step size LMS algorithm in which the step size varies inversely with the squared norm of the error vector. With an appropriate choice of the value of the fixed step size in the proposed algorithm, a trade-off between speed of convergence and misadjustment can be achieved. The performance of the proposed algorithm is compared
This paper introduces a new adaptive noise canceller (ANC) using a modified least mean-square (LM... more This paper introduces a new adaptive noise canceller (ANC) using a modified least mean-square (LMS) algorithm that applies nonlinearities to the error signal in the LMS update equation. The proposed algorithm for ANCs can be viewed as a variable step-size LMS algorithm, in which the step-size is inversely proportional to the square norm of the error vector which has an
Canadian Journal of Electrical and Computer Engineering, 2014
This paper introduces an adaptive noise canceller (ANC) using a proposed variable step size least... more This paper introduces an adaptive noise canceller (ANC) using a proposed variable step size least mean-square (LMS) algorithm. The step size varies between two hard limits based on a predetermined nonlinear decreasing function of signal to noise ratio (SNR) estimated at every iteration of the algorithm. The performance of the proposed algorithm is studied for different power levels of both stationary and nonstationary Gaussian noise added to the original speech. Compared with other several variable step size algorithms, computer simulations show performance superiority of the proposed algorithm in decreasing excess mean square error (EMSE) in both stationary and nonstationary noise environments. Simulations of the proposed method also show substantial improvements in decreasing misadjustment and reverberation.
Circuits, Systems, and Signal Processing, 2013
A new method to detect and reduce the impulse noise in color images is presented in this paper. T... more A new method to detect and reduce the impulse noise in color images is presented in this paper. The method consists of two stages: detection and filtering. Since each of the individual channels (components) of the color image can be considered as a monochrome image, both stages are applied to each channel separately, and then the individual results are combined into one output image. The corrupted pixels are detected in the first stage based on a proposed innovative switching technique. The noise-free pixels are copied to their corresponding locations in the output image. In the second stage, average filtering is applied only to those pixels which are determined to be noisy in the first stage, and only noise-free pixel values are involved in calculating this average. The size of the sliding window depends on the estimated noise density and is very small even for high noise densities. The proposed method is effective in noise reduction while preserving edge details and color chromaticity. Simulation results show that the proposed method outperforms all the tested existing state-of-the-art methods used in digital color image restoration in both standard objective measurements and perceived image quality.
Circuits, Systems, and Signal Processing, 2012
American Journal of Applied Sciences, 2008
TELKOMNIKA (Telecommunication Computing Electronics and Control)
In this paper, an impulse noise filtering technique for video signals using an adaptive size of s... more In this paper, an impulse noise filtering technique for video signals using an adaptive size of sliding window is presented. The video signal is first converted into frames and each frame is processed by the proposed video noise reduction technique as three separate components (colors). The noise reduction method is applied to all frames of the video. Four main stages are involved in this technique and applied to all frames of the video signal. In the first stage the video signal is separated into its frames and each frame is divided into its three primary color components. In the second stage, a decision-based algorithm is applied to each frame component where pixels in each component have to be determined whether or not they are noisy pixels. In the third stage, each noisy pixel is replaced by the median value of its neighborhood in an adaptive-size sliding window. The size of this window size is predetermined at the beginning of this stage and is dependent on an estimate value of the noise percentage. In the fourth stage, the three components of each frame are concatenated into a single frame, and all the frames are then combined back into a restored video signal. The performance of the proposed technique is tested through simulation experiments and applied to several movie signals contaminated with a wide range of impulsive noise percentages. The proposed technique shows superior results in terms of quantitative measures such as mean absolute error and peak-signal-to-noise ratio than many other existing techniques in the literature of video noise reduction.
In this paper, the effect of the kernel size of Wiener and Gaussian filters on their image restor... more In this paper, the effect of the kernel size of Wiener and Gaussian filters on their image restoration qualities has been studied and analyzed. Four sizes of such kernels, namely 3x3, 5x5, 7x7 and 9x9 were simulated. Two different types of noise with zero mean and several variances have been used: Gaussian noise and speckle noise. Several image quality measuring indices have been applied in the computer simulations. In particular, mean absolute error (MAE), mean square error (MSE) and structural similarity (SSIM) index were used. Many images were tested in the simulations; however the results of three of them are shown in this paper. The results show that the Gaussian filter has a superior performance over the Wiener filter for all values of Gaussian and speckle noise variances mainly as it uses the smallest kernel size. To obtain a similar performance in Wiener filtering, a larger kernel size is required which produces much more blur in the output mage. The Wiener filter shows poor performance using the smallest kernel size (3x3) while the Gaussian filter shows the best results in such case. With the Gaussian filter being used, similar results of those obtained with low noise could be obtained in the case of high noise variance but with a higher kernel size.
A new method to detect and reduce the impulse noise in color images is presented in this paper. T... more A new method to detect and reduce the impulse noise in color images is presented in this paper. The method consists of two stages: detection and filtering. Since each of the individual channels (components) of the color image can be considered as a monochrome image, both stages are applied to each channel separately, and then the individual results are combined into one output image. The corrupted pixels are detected in the first stage based on a proposed innovative switching technique. The noise-free pixels are copied to their corresponding locations in the output image. In the second stage, average filtering is applied only to those pixels which are determined to be noisy in the first stage, and only noise-free pixel values are involved in calculating this average. The size of the sliding window depends on the estimated noise density and is very small even for high noise densities. The proposed method is effective in noise reduction while preserving edge details and color chromaticity. Simulation results show that the proposed method outperforms all the tested existing state-of-the-art methods used in digital color image restoration in both standard objective measurements and perceived image quality.
In this paper, the quality performance of several filters in restoration of images corrupted with... more In this paper, the quality performance of several filters in restoration of images corrupted with various types of noise has been examined extensively. In particular, Wiener filter, Gaussian filter, median filter and averaging (mean) filter have been used to reduce Gaussian noise, speckle noise, salt and pepper noise and Poisson noise. Many images have been tested, two of which are shown in this paper. Several percentages of noise corrupting the images have been examined in the simulations. The size of the sliding window is the same in the four filters used, namely 5x5 for all the indicated noise percentages. For image quality measurement, two performance measuring indices are used: peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The simulation results show that the performance of some specific filters in reducing some types of noise are much better than others. It has been illustrated that median filter is more appropriate for eliminating salt and pepper noise. Averaging filter still works well for such type of noise, but of less performance quality than the median filter. Gaussian and Wiener filters outperform other filters in restoring mages corrupted with Poisson and speckle noise.
Adaptive Filtering Primer With Matlab®
... Zayed M. Ramadan received his BS and MS degrees in electrical engineer-ing (EE) from Jordan U... more ... Zayed M. Ramadan received his BS and MS degrees in electrical engineer-ing (EE) from Jordan University of Science and Technology in ... signal processing 5 2.1 Discrete-time signals 5 2.2 Transform-domain representation of discrete-time signals 5 2.3 The Z-Transform 11 2.4 ...
TELKOMNIKA (Telecommunication Computing Electronics and Control)
In this paper, the effect of the kernel size of Wiener and Gaussian filters on their image restor... more In this paper, the effect of the kernel size of Wiener and Gaussian filters on their image restoration qualities has been studied and analyzed. Four sizes of such kernels, namely 3x3, 5x5, 7x7 and 9x9 were simulated. Two different types of noise with zero mean and several variances have been used: Gaussian noise and speckle noise. Several image quality measuring indices have been applied in the computer simulations. In particular, mean absolute error (MAE), mean square error (MSE) and structural similarity (SSIM) index were used. Many images were tested in the simulations; however the results of three of them are shown in this paper. The results show that the Gaussian filter has a superior performance over the Wiener filter for all values of Gaussian and speckle noise variances mainly as it uses the smallest kernel size. To obtain a similar performance in Wiener filtering, a larger kernel size is required which produces much more blur in the output mage. The Wiener filter shows poor performance using the smallest kernel size (3x3) while the Gaussian filter shows the best results in such case. With the Gaussian filter being used, similar results of those obtained with low noise could be obtained in the case of high noise variance but with a higher kernel size.
American Journal of Engineering and Applied Sciences
American Journal of Signal Processing, 2014
This paper introduces a new variable step-size LMS algorithm in which the step-size is dependent ... more This paper introduces a new variable step-size LMS algorithm in which the step-size is dependent on both data and error normalization. With an appropriate choice of the value of the fixed step-size and the ratio between error and data normalization in the proposed algorithm, a trade-off between speed of convergence and misadjustment can be achieved. The performance of the algorithm
Southeastern Symposium on System Theory, 2004
This paper introduces a new variable step size LMS algorithm in which the step size varies invers... more This paper introduces a new variable step size LMS algorithm in which the step size varies inversely with the squared norm of the error vector. With an appropriate choice of the value of the fixed step size in the proposed algorithm, a trade-off between speed of convergence and misadjustment can be achieved. The performance of the proposed algorithm is compared
This paper introduces a new adaptive noise canceller (ANC) using a modified least mean-square (LM... more This paper introduces a new adaptive noise canceller (ANC) using a modified least mean-square (LMS) algorithm that applies nonlinearities to the error signal in the LMS update equation. The proposed algorithm for ANCs can be viewed as a variable step-size LMS algorithm, in which the step-size is inversely proportional to the square norm of the error vector which has an
Canadian Journal of Electrical and Computer Engineering, 2014
This paper introduces an adaptive noise canceller (ANC) using a proposed variable step size least... more This paper introduces an adaptive noise canceller (ANC) using a proposed variable step size least mean-square (LMS) algorithm. The step size varies between two hard limits based on a predetermined nonlinear decreasing function of signal to noise ratio (SNR) estimated at every iteration of the algorithm. The performance of the proposed algorithm is studied for different power levels of both stationary and nonstationary Gaussian noise added to the original speech. Compared with other several variable step size algorithms, computer simulations show performance superiority of the proposed algorithm in decreasing excess mean square error (EMSE) in both stationary and nonstationary noise environments. Simulations of the proposed method also show substantial improvements in decreasing misadjustment and reverberation.
Circuits, Systems, and Signal Processing, 2013
A new method to detect and reduce the impulse noise in color images is presented in this paper. T... more A new method to detect and reduce the impulse noise in color images is presented in this paper. The method consists of two stages: detection and filtering. Since each of the individual channels (components) of the color image can be considered as a monochrome image, both stages are applied to each channel separately, and then the individual results are combined into one output image. The corrupted pixels are detected in the first stage based on a proposed innovative switching technique. The noise-free pixels are copied to their corresponding locations in the output image. In the second stage, average filtering is applied only to those pixels which are determined to be noisy in the first stage, and only noise-free pixel values are involved in calculating this average. The size of the sliding window depends on the estimated noise density and is very small even for high noise densities. The proposed method is effective in noise reduction while preserving edge details and color chromaticity. Simulation results show that the proposed method outperforms all the tested existing state-of-the-art methods used in digital color image restoration in both standard objective measurements and perceived image quality.
Circuits, Systems, and Signal Processing, 2012
American Journal of Applied Sciences, 2008
TELKOMNIKA (Telecommunication Computing Electronics and Control)
In this paper, an impulse noise filtering technique for video signals using an adaptive size of s... more In this paper, an impulse noise filtering technique for video signals using an adaptive size of sliding window is presented. The video signal is first converted into frames and each frame is processed by the proposed video noise reduction technique as three separate components (colors). The noise reduction method is applied to all frames of the video. Four main stages are involved in this technique and applied to all frames of the video signal. In the first stage the video signal is separated into its frames and each frame is divided into its three primary color components. In the second stage, a decision-based algorithm is applied to each frame component where pixels in each component have to be determined whether or not they are noisy pixels. In the third stage, each noisy pixel is replaced by the median value of its neighborhood in an adaptive-size sliding window. The size of this window size is predetermined at the beginning of this stage and is dependent on an estimate value of the noise percentage. In the fourth stage, the three components of each frame are concatenated into a single frame, and all the frames are then combined back into a restored video signal. The performance of the proposed technique is tested through simulation experiments and applied to several movie signals contaminated with a wide range of impulsive noise percentages. The proposed technique shows superior results in terms of quantitative measures such as mean absolute error and peak-signal-to-noise ratio than many other existing techniques in the literature of video noise reduction.
In this paper, the effect of the kernel size of Wiener and Gaussian filters on their image restor... more In this paper, the effect of the kernel size of Wiener and Gaussian filters on their image restoration qualities has been studied and analyzed. Four sizes of such kernels, namely 3x3, 5x5, 7x7 and 9x9 were simulated. Two different types of noise with zero mean and several variances have been used: Gaussian noise and speckle noise. Several image quality measuring indices have been applied in the computer simulations. In particular, mean absolute error (MAE), mean square error (MSE) and structural similarity (SSIM) index were used. Many images were tested in the simulations; however the results of three of them are shown in this paper. The results show that the Gaussian filter has a superior performance over the Wiener filter for all values of Gaussian and speckle noise variances mainly as it uses the smallest kernel size. To obtain a similar performance in Wiener filtering, a larger kernel size is required which produces much more blur in the output mage. The Wiener filter shows poor performance using the smallest kernel size (3x3) while the Gaussian filter shows the best results in such case. With the Gaussian filter being used, similar results of those obtained with low noise could be obtained in the case of high noise variance but with a higher kernel size.
A new method to detect and reduce the impulse noise in color images is presented in this paper. T... more A new method to detect and reduce the impulse noise in color images is presented in this paper. The method consists of two stages: detection and filtering. Since each of the individual channels (components) of the color image can be considered as a monochrome image, both stages are applied to each channel separately, and then the individual results are combined into one output image. The corrupted pixels are detected in the first stage based on a proposed innovative switching technique. The noise-free pixels are copied to their corresponding locations in the output image. In the second stage, average filtering is applied only to those pixels which are determined to be noisy in the first stage, and only noise-free pixel values are involved in calculating this average. The size of the sliding window depends on the estimated noise density and is very small even for high noise densities. The proposed method is effective in noise reduction while preserving edge details and color chromaticity. Simulation results show that the proposed method outperforms all the tested existing state-of-the-art methods used in digital color image restoration in both standard objective measurements and perceived image quality.
In this paper, the quality performance of several filters in restoration of images corrupted with... more In this paper, the quality performance of several filters in restoration of images corrupted with various types of noise has been examined extensively. In particular, Wiener filter, Gaussian filter, median filter and averaging (mean) filter have been used to reduce Gaussian noise, speckle noise, salt and pepper noise and Poisson noise. Many images have been tested, two of which are shown in this paper. Several percentages of noise corrupting the images have been examined in the simulations. The size of the sliding window is the same in the four filters used, namely 5x5 for all the indicated noise percentages. For image quality measurement, two performance measuring indices are used: peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The simulation results show that the performance of some specific filters in reducing some types of noise are much better than others. It has been illustrated that median filter is more appropriate for eliminating salt and pepper noise. Averaging filter still works well for such type of noise, but of less performance quality than the median filter. Gaussian and Wiener filters outperform other filters in restoring mages corrupted with Poisson and speckle noise.