Hamid Amiri

Work place: Department of Electrical Engineering, University of Tunis El Manar, Tunisia

E-mail: hamidlamiri@gmail.com

Website: https://www.researchgate.net/profile/Hamid-Amiri

Research Interests: Comparative Programming Language Analysis, Programming Language Theory, Graph and Image Processing, Natural Language Processing, Image Processing, Speech Recognition, Speech Synthesis


Pr. Hamid Amiri, received the Diploma of Electrotechnics, Information Technique in 1978 and the PHD degree in1983 at the at the TU Braunschweig, Germany. He obtained the Doctorates Sciences in1993. He was a Professor at the National Engineering High School of Tunisia, from 1987 to 2001. From 2001 to 2009 he was at the Riyadh College of Telecom and Information. Currently, he is again at the National Engineering High School of Tunisia. He is now Director of Signal Processing Research Laboratory LSTS, and is in charge of Control and Signal Processing Master degree at this National Engineering High School. His research is focused on: image processing, speech processing, document processing and natural language processing.

Author Articles
Wavelet-based Video Coding using Advanced Fractional Motion Estimation Technique

By Wissal Hassen Hamid Amiri

DOI: https://doi.org/10.5815/ijigsp.2015.08.08, Pub. Date: 8 Jul. 2015

The purpose of this paper is to encode a color video by wavelet transformation. Therefore, we propose a new hybrid approach which combines a fractional motion estimation technique. Several studies were carried out to reduce the spatial and temporal redundancies, hence at the level of spatial video coding, we use a new approach based on sub-bands coding through a discrete wavelet transformation. This technique is based on the principle of the EZW algorithm of Shapiro. It proceeds by separating the encoding of the signs and the magnitudes of wavelet coefficients. Then, at the level of temporal compression, we propose a study of motion estimation with different accuracy based on image interpolation to improve the quality of predicted frame. Next, we present a representation reducing the size of the motion vector field and we compress it by two of entropic coding approaches namely Huffman coding and arithmetic coding.
The proposed video codec was applied on a video sequence with different sizes (CIF and QCIF) and different dynamics. The obtained results, in terms of objective assessment (PSNR, the SSIM and VQM), were satisfactory compared with other video coding standards. We have also proposed a subjective evaluation and the results are compared to those obtained by H.264/AVC standard.

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