Ali Radmehr | Isfahan University of Technology (original) (raw)
Address: Iran, Islamic Republic of
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Umm Al-Qura University, Makkah, Saudi Arabia
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Papers by Ali Radmehr
Multimedia Tools and Applications
Zenodo (CERN European Organization for Nuclear Research), Nov 29, 2022
Signal, Image and Video Processing, 2015
We use particle filtering for correcting the erroneous Motion Vectors (MVs) which are derived fro... more We use particle filtering for correcting the erroneous Motion Vectors (MVs) which are derived from the Boundary Matching Algorithm (BMA) in packet video communications. Assuming a two-state Markov channel model for transmission, the error of the extracted MVs by BMA is shown to be modeled by the Gaussian Mixture (GM) distribution. Formulating the problem in the state-space, we deploy particle filtering for denoising the erroneous MVs. The main challenge of using particle filters is high computational complexity that is directly related to the number of particles. The proposed particle filtering scheme is efficient even if the number of particles is decreased. Experimental results are provided to show the efficiency of this filtering approach compared to a recent scheme based on Kalman filtering. The experiments show meaningful increase in the quality of the recovered video sequences in terms of PSNR up to 3 dB compared with the other error concealment (EC) techniques. Also, the computational complexity of the proposed scheme is discussed.
2013 21st Iranian Conference on Electrical Engineering (ICEE), 2013
Video transmission over wireless networks becomes a major part of multimedia studies especially a... more Video transmission over wireless networks becomes a major part of multimedia studies especially after fourthgeneration communication standard has been introduced. There is a growing need to improve video visual quality, while its computational complexity should remain low. A low-complexity Error Concealment (EC) method for missing macroblock (MB) recovery is Boundary Matching Algorithm (BMA). Nevertheless, this method suffers from lack of accuracy. In this paper, we propose a novel modified BMA method by exploiting the correlation of the pixels on the edge of the missing MB. The performance of this method is explained in detail and extra experiment results are given to demonstrate its superiority over BMA method.
2014 22nd Iranian Conference on Electrical Engineering (ICEE), 2014
Error Concealment (EC) algorithms have provided a very useful tool for concealing the errors in d... more Error Concealment (EC) algorithms have provided a very useful tool for concealing the errors in digital video streams. The importance of EC methods arises specially in broadcasting and multicasting communications where retransmission of corrupted video sequence is not possible. In this paper, a Motion Vector (MV) space is proposed around each erroneous macroblock (MB) and thus the candidate MV can be refined using a Gaussian window effectively. Gaussian window application in this scenario is analyzed in detail. Finally, simulation results proves the superiority of the proposed method to the conventional approaches.
Multimedia Tools and Applications
Zenodo (CERN European Organization for Nuclear Research), Nov 29, 2022
Signal, Image and Video Processing, 2015
We use particle filtering for correcting the erroneous Motion Vectors (MVs) which are derived fro... more We use particle filtering for correcting the erroneous Motion Vectors (MVs) which are derived from the Boundary Matching Algorithm (BMA) in packet video communications. Assuming a two-state Markov channel model for transmission, the error of the extracted MVs by BMA is shown to be modeled by the Gaussian Mixture (GM) distribution. Formulating the problem in the state-space, we deploy particle filtering for denoising the erroneous MVs. The main challenge of using particle filters is high computational complexity that is directly related to the number of particles. The proposed particle filtering scheme is efficient even if the number of particles is decreased. Experimental results are provided to show the efficiency of this filtering approach compared to a recent scheme based on Kalman filtering. The experiments show meaningful increase in the quality of the recovered video sequences in terms of PSNR up to 3 dB compared with the other error concealment (EC) techniques. Also, the computational complexity of the proposed scheme is discussed.
2013 21st Iranian Conference on Electrical Engineering (ICEE), 2013
Video transmission over wireless networks becomes a major part of multimedia studies especially a... more Video transmission over wireless networks becomes a major part of multimedia studies especially after fourthgeneration communication standard has been introduced. There is a growing need to improve video visual quality, while its computational complexity should remain low. A low-complexity Error Concealment (EC) method for missing macroblock (MB) recovery is Boundary Matching Algorithm (BMA). Nevertheless, this method suffers from lack of accuracy. In this paper, we propose a novel modified BMA method by exploiting the correlation of the pixels on the edge of the missing MB. The performance of this method is explained in detail and extra experiment results are given to demonstrate its superiority over BMA method.
2014 22nd Iranian Conference on Electrical Engineering (ICEE), 2014
Error Concealment (EC) algorithms have provided a very useful tool for concealing the errors in d... more Error Concealment (EC) algorithms have provided a very useful tool for concealing the errors in digital video streams. The importance of EC methods arises specially in broadcasting and multicasting communications where retransmission of corrupted video sequence is not possible. In this paper, a Motion Vector (MV) space is proposed around each erroneous macroblock (MB) and thus the candidate MV can be refined using a Gaussian window effectively. Gaussian window application in this scenario is analyzed in detail. Finally, simulation results proves the superiority of the proposed method to the conventional approaches.