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Eltaweel S.G.,National Telecommunication Institute NTI
2013 9th International Computer Engineering Conference: Today Information Society What's Next?, ICENCO 2013

In this paper, we have a mixture of two added images and it is required to separate the two image sources from the combined one after receiving the combined image and one of the two source images. The Discrete Wavelet Transform (DWT) is applied on the combined image. Also, it is applied on the corrupted and received image source. The high frequency components of the combined image and the image source are correlated. The result of correlation is used in classifying the pixel whether belongs to image source or zero. The experiment is applied on the other image source and the combined image. The performance is measured and compared to a recent paper in the same topic and the proposed method is proved to have better results than the results of the recent paper. In the recent paper, the color mixture is not considered, it is considered in our work and gave very good results. © 2013 IEEE. Source

El-Hennawy H.M.,Ain Shams University | Gomaa H.H.,Ain Shams University | Amin A.S.,National Telecommunication Institute NTI
ICT 2010: 2010 17th International Conference on Telecommunications

Internet Protocol version 6 (IPv6) is a new protocol that has been defined to ultimately replace IPv4. IPv6 solves the problem imposed by the limited 32-bit address field in IPv4. However the definition of the new protocol results in longer header size, which affects services that used to be transmitted over IP especially real-time services such as voice. As IP network is no longer confined to the wired domain and is being extended over wireless networks. The IEEE 802.16-based WiMAX (World Wide Interoperability of Microwave Access) promises to be one of the wireless access technologies capable of supporting very high bandwidth applications. In this paper, using the simulation results obtained by NS2, we demonstrate the effectiveness of transmitting voice traffic over IPv6 convergence sublayer of WiMAX mesh network and compare it with the quality in case of applying current header compression techniques, Robust Header Compression (ROHC) and Payload Header Suppression (PHS), and a new proposed modification to the PHS technique. We prove that using our proposed technique we improve the current PHS technique and approach the same performance of ROHC technique. © 2009 IEEE. Source

Eltaweel S.G.,National Telecommunication Institute NTI
ICENCO'2011 - 2011 7th International Computer Engineering Conference: Today Information Society What's Next?

In this paper a new technique is introduced to hide nine images in a color image. The color image has size four as the watermark size. In each of the color image components three images are hidden. Each color component is decomposed by a Discrete Wavelet Transform (DWT) into four components. Three of four components are used to hide the three images. The hiding operation starts with taking the Discrete Cosine Transform (DCT) for the watermark and the result is multiplied by a factor and added to a component of the three components which result from the DWT decomposition. The Inverse DWT (IDWT) is applied to reconstruct the red, green and blue components. Finally, the result is the reconstruction from the main components. The extraction process is considered in the theory of statistical signal processing as a correlation receiver. The correlation is calculated to decide each pixel is a watermark pixel or not. Different types of images are used as watermarks. The results show the robustness of the technique, the SNR obtained is at least 25 dB. © 2011 IEEE. Source

El Zorkany M.,National Telecommunication Institute NTI
Advances in Intelligent Systems and Computing

Image and video transmissions require particularly large bandwidth and storage space. Image compression technology is therefore essential to overcome these problems. Practically efficient compression systems based on hybrid coding which combines the advantages of different methods of image coding have also being developed over the years. In this paper, different hybrid approaches to image compression are discussed. Hybrid coding of images, in this research, deals with combining three approaches to enhance the individual methods and achieve better quality reconstructed images with higher compression ratio. In this paper A new Hybrid neural-network, vector quantization and discrete cosine transform compression method is presented. This scheme combines the high compression ratio of Neural network (NN) and Vector Quantization (VQ) with the good energy-compaction property of Discrete Cosine Transform(DCT). In order to increase the compression ratio while preserving decent reconstructed image quality, Image is compressed using Neural Network, then take the hidden layer outputs as input to re-compress it using vector quantization (VQ), while DCT was used the code books block. Simulation results show the effectiveness of the proposed method. The performance of this method is compared with the available jpeg compression technique over a large number of images, showing good performance. © Springer International Publishing Switzerland 2014. Source

Farrag W.,Al - Azhar University of Egypt | Ragheb A.N.,National Telecommunication Institute NTI | Rashid N.,Al - Azhar University of Egypt
National Radio Science Conference, NRSC, Proceedings

This paper presents a design of Low Noise Amplifier (LNA) for Cognitive Radios (CRs) receiver and it operates from 50 MHz to 5 GHz. The proposed design is consisted of two stages; the first one is a combination of cascode with common gate stage to improve the gain, power consumption, and the input matching. The second stage is a common source (CS) for cancelling the noise and distortion of CG of the first stage. This design achieves a noise figure 4.1-4.8 dB, input reflection coefficient less than-11 dB, output reflection coefficient below-10 dB, the power gain from 10.2 dB to 12.5 dB and the power consumption 7.14 mW supplied from 1 V. The proposed LNA is designed using 0.18 μm CMOS technology. © 2014 IEEE. Source

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