S. M. Mahbubur Rahman, Ph.D.              Assistant Professor Department of EEE, BUET  Telephone: +88-02-966-5650 Ext 6053 (Off)             +88-02-966-5650 Ext 7919 (Res)            +88-0182-393-3902 (Cell) E-mail: mahbubur@eee.buet.ac.bd             mahbuburbd@gmail.com

Biography:

Publications:

Articles Accepted or Published in Journals:

1.      Nafi Ur Rashid, Niluthpol Chowdhury Mithun, and S. M. Mahbubur Rahman, ''Detection and classification of vehicles from video using multiple time-spatial images,'' in press of IEEE Transactions on Intelligent Transportation Systems, DOI (identifier) 10.1109/TITS.2012.2186128, Jan. 2012.

2.    Sanjit Roy, Tamanna Howlader, and S. M. Mahbubur Rahman, ''Image fusion technique using multivariate statistical model for wavelet coefficients,'' in press and available online, Signal Image and Video Processing, Springer, July 2011.

3.     S. M. Mahbubur Rahman, M. Omair Ahmad, and M. N. S. Swamy, ''Contrast-based fusion of noisy images using discrete wavelet transform,'' IET Image Processing, vol. 4, no. 5, pp. 374-384, May 2010.

4.       S. M. Mahbubur Rahman, M. Omair Ahmad, and M. N. S. Swamy, ''A new statistical detector for DWT-based additive image watermarking using the Gauss-Hermite expansion,'' IEEE Transactions on Image Processing, vol. 18, no. 8, pp. 1782-1796, Aug. 2009.

5.        S. M. Mahbubur Rahman, M. Omair Ahmad, and M. N. S. Swamy, ''Bayesian wavelet-based image denoising using the Gauss-Hermite expansion,'' IEEE Transactions on Image Processing, vol. 17, no. 10, pp. 1755-1771, Oct. 2008.

6.        S. M. Mahbubur Rahman, M. Omair Ahmad, and M. N. S. Swamy, ''Statistics of 2D DT-CWT coefficients for Gaussian distributed signal,'' IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 55, no. 7, pp. 2013-2025, Aug. 2008.

7.        S. M. Mahbubur Rahman, M. Omair Ahmad, and M. N. S. Swamy, ''Video denoising based on inter-frame statistical modeling of the wavelet coefficients,'' IEEE Transactions on Circuits and Systems for Video Technology, vol. 17, no. 2, pp. 187-198, Feb. 2007.

8.        S. M. Mahbubur Rahman and Md. Kamrul Hasan, ''Wavelet-domain iterative center weighted median filter for image denoising,'' Signal Processing, Elsevier Science Publishers, vol. 83, no. 5, pp. 1001-1012, May 2003.

Articles Submitted in Journals:

1.  Md Mushfiqul Alam, Tamanna Howlader, and S. M. Mahbubur Rahman, ''Entropy-based image registration method using the curvelet transform,'' submitted in Image and Vision Computing, Elsevier Science Publishers, paper number - IMAVIS-D-12-00007, Jan. 2012.

Articles Published in Proceedings of Conferences:

1.       Nafi Ur Rashid, Niluthpol Chowdhury Mithun, Bhadhan Roy Joy,  and S. M. Mahbubur Rahman, ''Detection and classification of vehicles from a video using time-spatial image,'' in Proceedings of 6^th International Conference on Electrical and Computer Engineering, Dhaka, Bangladesh, pp. 502-505, Dec. 2010.

2.       S. M. Mahbubur Rahman, M. Omair Ahmad, and M. N. S. Swamy, ''A new bivariate MAP estimator for DT-CWT-based video denoising,'' in Proceedings of 42^nd IEEE International Symposium on Circuits and Systems, Taipei, Taiwan, Republic of China, pp. 517-520, May 2009.

3.       S. M. Mahbubur Rahman, M. Omair Ahmad, and M. N. S. Swamy, ''A new contrast-based fusion scheme for noisy images using wavelet transform,'' in Proceedings of 1^st International Symposium on Digital Life Technologies, Tainan, Taiwan, Republic of China, pp. 108-111, May 2009.

4.       S. M. Mahbubur Rahman, M. Omair Ahmad, and M. N. S. Swamy, ''Improved image restoration using wavelet-based denoising and Fourier-based deconvolution,'' in Proceedings of 51^st IEEE International Mid-West Symposium on Circuits and Systems, Knoxville, TN, USA, pp. 249-252, Aug. 2008.

5.       S. M. Mahbubur Rahman, M. Omair Ahmad, and M. N. S. Swamy, ''Statistical detector for wavelet-based image watermarking using modified GH PDF,'' in Proceedings of 41^st IEEE International Symposium on Circuits and Systems, Seattle, WA, USA, pp. 712-715, May 2008.

6.       S. M. Mahbubur Rahman, M. Omair Ahmad, and M. N. S. Swamy, ''Locally adaptive wavelet-based image denoising using the Gram-Charlier prior function,'' in Proceedings of 14^th IEEE International Conference on Image Processing, San Antonio, TX, USA, vol. 3, pp. 549-552, Sep. 2007.

7.       S. M. Mahbubur Rahman, M. Omair Ahmad, and M. N. S. Swamy, ''Bayesian wavelet-based despeckling of ultrasound medical images using the Gauss-Hermite expansion,'' in Proceedings of 8^th Joint Statistical Meetings, Salt Lake City, UT, USA, pp. 1718-1725, Jul. 2007.

8.       S. M. Mahbubur Rahman, M. Omair Ahmad, and M. N. S. Swamy, ''Wavelet-based video denoising using Gauss-Hermite density function,'' in Proceedings of 49^th IEEE International Mid-West Symposium on Circuits and Systems, San Juan, PR, USA, vol. 1, pp. 592-595, Aug. 2006.

9.       S. M. Mahbubur Rahman, M. Omair Ahmad, and M. N. S. Swamy, ''Wavelet-domain image denoising algorithm using series expansion of coefficient p.d.f. in terms of Hermite polynomials,'' in Proceedings of 3^rd International IEEE North-East Workshop on Circuits and Systems, Quebec City, QC, Canada, pp. 271-275, Jun. 2005.

10.   S. M. Mahbubur Rahman and Md. Kamrul Hasan, ''Improved wavelet-based image denoising algorithm using iterative center weighted median filter,'' in Proceedings of 3^rd International Symposium on Communication System, Network and Digital Signal Processing, Staffordshire, UK, pp. 304-307, Jul. 2002.

11.   M. R. Huq, M. I. H. Bhuiyan, M. M. Rahman, S. M. M. Rahman, and M. K. Hasan, ''An improved memoryless vector quantizer using LBG algorithm and neural networks for image compression,'' in Proceedings of 3^rd International Symposium on Communication System, Network and Digital Signal Processing, Staffordshire, UK, pp. 264-267, Jul. 2002.

Teaching:

Students (Research):

Notice:

I am continuously looking for potential or existing postgraduate students those have interests to pursue their thesis in the area of visual signal processing to work with me. My research interests include the challenging issues of modeling and processing techniques of visual signals for various applications in biomedical engineering (e.g., ultrasound, MRI, and CT), geoscience (e.g., SAR), genetics (e.g., microarray) and communication. The research directions would be:

• Development of mathematically tractable and computationally efficient probabilistic or mathematical models for the visual signals that describe the essential variability of a signal such as motion in a video.

• Application of these models in various real-world processing techniques such as reduction of noise and speckle, restoration, registration, fusion, detection of edge and texture, enhancement, copyright protection, encryption, compression, classification, pattern recognition, stabilization, and segmentation.

• Statistical analysis of these signals in the space-time and various transform domains such as the DFT, DCT, wavelet, and curvelet in their multidimensional representations e.g., 2D and 3D.