As an extension of H.264/AVC, Scalable Video Coding (SVC) provides the ability to adapt to heterogeneous networks and user-end requirements, which offers great scalability in multi-point applications such as videoconferencing. However, transcoding between SVC and AVC becomes necessary due to the existence of legacy AVC-based systems. The straightforward full re-encoding method requires great computational cost, and the fast SVC-to-AVC spatial transcoding techniques have not been thoroughly investigated yet. This paper proposes a low-complexity hybrid-domain SVC-to-AVC spatial transcoder with drift compensation, which provides even better coding efficiency than the full re-encoding method. The macroblocks (MBs) of input SVC bitstream are divided into two types, and each type is suitable for pixel- or transform-domain processing respectively. In the pixel-domain transcoding, a fast re-encoding method is proposed based on mode mapping and motion vector (MV) refinement. In the transform-domain transcoding, the quantized transform coefficients together with other motion data are reused directly to avoid re-quantization loss. The drift problem caused by proposed transcoder is solved by compensation techniques for I frame and P frame respectively. Simulation results show that proposed transcoder achieves averagely 96.4% time reduction compared with the full re-encoding method, and outperforms the reference methods in coding efficiency.

An alternative polynomial expansion for electromagnetic field estimation inside three-dimensional dielectric scatterers is presented in this article. In a continuation with the previous work of authors, the Tensor-Volume Integral Equation (TVIE) is solved by using the Galerkin-based moment method (MoM) consisting of a combination of entire-domain and sub-domain basis functions including three-dimensional polynomials. Instead of using trivial power polynomials, Legendre polynomials are adopted for electromagnetic fields expansion in this study. They have the advantage of being a set of orthogonal functions, which allows the use of high-order basis functions without introducing an ill-condition MoM matrix. The accuracy of such approach in MoM is verified by comparing its numerical results with that of exact analytical method such as Mie theory and conventional procedures in MoM. Besides, it is also confirmed that the condition number of the MoM matrix obtained with the proposed approach is lower than that of the previous approaches.