Abdelrahman Abdelazim

Embedded devices for supply chain applications: Towards hardware integration of disparate technologies

The emergence of the RFID technology and its application to supply chain processes has in particular led to the creation of such standards as the EPCglobals model of supply networks as a tool for materializing intra- and inter-enterprise visibility of resources and products, collaboration and integration. Among other critical uses, RFID has been deployed by supply networks to improve asset utilization, effectively combat counterfeiting, and advance targeted product recalls. However, new affordable and deployable technologies and microsensors have recently appeared and keep maturing. This paper discusses the needs and the possibilities that exist for leveraging these technologies and sensors with RFID to guarantee continuous and seamless visibility of all assets (fixed and mobile resources and field personnel) of smart enterprises, thereby expanding and complementing the roles of RFID. It examines the design challenges for the integration of these technologies for advanced logistics operations at the level of product classes or their instances. It then outlines our development of an embedded microsystem that combines RFID, GPRS, GPS and environmental sensors for applications in logistics. The prototyped microsystem demonstrated the feasibility of the multi-sensor integration paradigm that the paper proposes.

Fast prediction algorithm for multiview video coding

Abstract. The H.264/multiview video coding (MVC) standard has been developed to enable efficient coding for three-dimensional and multiple viewpoint video sequences. The inter-view statistical dependencies are utilized and an inter-view prediction is employed to provide more efficient coding; however, this increases the overall encoding complexity. Motion homogeneity is exploited here to selectively enable inter-view prediction, and to reduce complexity in the motion estimation (ME) and the mode selection processes. This has been accomplished by defining situations that relate macro-blocks’ motion characteristics to the mode selection and the inter-view prediction processes. When comparing the proposed algorithm to the H.264/MVC reference software and other recent work, the experimental results demonstrate a significant reduction in ME time while maintaining similar rate-distortion performance.

Fast subpixel motion estimation based on the interpolation effect on different block sizes for H264/AVC

We propose a fast subpixel motion estimation algorithm for the H.264 advanced video coding (AVC) standard. The algorithm utilizes the correlation of the spatial interpolation effect on the full-pixel motion estimation best matches between different block sizes in order to reduce the computational cost of the overall motion-estimation process. Experimental results show that the proposed algorithm significantly reduces the CPU cycles in the various motion estimation schemes by up to 16% with similar rate-distortion performance when weighed up against the H.264/AVC standard.

Pixel decimation of RD-cost functions in the HEVC encoder

We present and analyse schemes for the improvement of computational complexity in the current HEVC (High Efficiency Video Coding) standard, by a subsampling of the block-matching distortion cost functions used in the encoding process. HEVC improves on prior standards considerably in coding (compression) efficiency, with a large set-back in time complexity for inter and intra prediction processes and mode decisions. We alleviate this by reducing the number of calculations per decision in all modes of prediction, through pixel decimation in the SAD and SSE distortion cost functions. Experimentation with different patterns shows significant encoding time reduction with these schemes, used in tandem with built-in Fast Encoding optimizations in the HEVC reference implementation.

Motion estimation optimization tools for the emerging high efficiency video coding (HEVC)

Recent development in hardware and software allowed a new generation of video quality. However, the development in networking and digital communication is lagging behind. This prompted the establishment of the Joint Collaborative Team on Video Coding (JCT-VC), with an objective to develop a new high-performance video coding standard. A primary reason for developing the HEVC was to enable efficient processing and transmission for HD videos that normally contain large smooth areas; therefore, the HEVC utilizes larger encoding blocks than the previous standard to enable more effective encoding, while smaller blocks are still exploited to encode fast/complex areas of video more efficiently. Hence, the implementation of the encoder investigates all the possible block sizes. This and many added features on the new standard have led to significant increase in the complexity of the encoding process. Furthermore, there is not an automated process to decide on when large blocks or small blocks should be exploited. To overcome this problem, this research proposes a set of optimization tools to reduce the encoding complexity while maintaining the same quality and compression rate. The method automates this process through a set of hierarchical steps yet using the standard refined coding tools.

Fast Adaptive Hierarchical Prediction Algorithm for H.264/AVC Scalable Video Coding

The objective of scalable video coding (SVC) is to enable the generation of a unique bitstream that can adapt to various bit-rates, transmission channels and display capabilities. The scalability is categorised in terms of temporal, spatial, and quality. In order to improve encoding efficiency, the SVC scheme incorporates inter-layer prediction mechanisms to complement the H.264/AVC very refined Motion Estimation (ME) and mode decision processes. However, this further increases the overall encoding complexity of the scalable coding standard. In this paper several conditional probabilities are established relating motion estimation characteristics and the mode distribution at different layers of the H.264/SVC. An evaluation of these probabilities is used to structure a low-complexity prediction algorithm for Group of Pictures (GOP) in H.264/SVC, reducing computational complexity whilst maintaining similar RD performance. When compared to the JSVM software, the proposed algorithm achieves a significant reduction of encoding time, with a negligible average PSNR loss and bit-rate increase in temporal, spatial and SNR scalability. Experiments are conducted to provide a comparison between our method and recently developed fast mode selection algorithms. These demonstrate the proposed method achieves appreciable time savings for scalable spatial and scalable quality video coding, while maintaining similar PSNR and bit rate.

Fast mode decision for the H.264/AVC video coding standard based on frequency domain motion estimation

The H.264 video coding standard achieves high performance compression and image quality at the expense of increased encoding complexity. Consequently, several fast mode decision and motion estimation techniques have been developed to reduce the computational cost. These approaches successfully reduce the computational time by reducing the image quality and/or increasing the bitrate. In this paper we propose a novel fast mode decision and motion estimation technique. The algorithm utilizes preprocessing frequency domain motion estimation in order to accurately predict the best mode and the search range. Experimental results show that the proposed algorithm significantly reduces the motion estimation time by up to 97%, while maintaining similar rate distortion performance when compared to the Joint Model software.

Low Complexity Hierarchical Prediction Algorithm for H.264/SVC

In the scalable video coding extension of the H.264/AVC standard, an exhaustive search technique is used to select the best coding mode for each macroblock. This technique achieves the highest possible coding efficiency, but it demands a higher video encoding computational complexity which constrains its use in many practical applications. This paper proposes combined fast sub-pixel motion estimation and a fast mode decision algorithm for inter-frame coding for temporal, spatial, and coarse grain signal-to-noise ratio scalability. It makes use of correlation between the macroblock and its enclosed partitions at different layers. Experimental results show that the scheme reduces the computational complexity significantly with negligible coding loss and bit-rate increases when compared to JSVM 9.15 and recently reported fast mode decision algorithms.

Selective application of sub-pixel motion estimation and Hadamard transform in H.264/AVC

In this paper, we propose an algorithm for selective application of sub-pixel Motion Estimation and Hadamard transform in the H.264/AVC video coding standard. The algorithm exploits the spatial interpolation effect of the reference slices on the best matches of different block sizes in order to increase the computational efficiency of the overall motion estimation process. Experimental results show that the proposed algorithm significantly reduces the CPU cycles in the Fast-Full-Search Motion Estimation Scheme by up to 8.2% with similar RD performance, as compared to the H.264/AVC standard.

Diamond frequency domain inter frame motion estimation for HEVC

This paper presents an efficient algorithm for motion estimation to reduce High Efficiency Video Coding (HEVC) standard encoding complexity. Phase correlation is initially utilized as a preprocessing step to indicate an approximation of the shift between coding units in the current frame and the reference frame. This is followed by a 9-point diamond search centered on the shift found in the initial step, in order to refine the best matching block. The proposed method has the potential to yield substantial improvements in terms of execution time and resulting video quality in comparison to the traditional search methods.