When the frame size is downscaled for video transcoding, the new motion vector (MV) must be computed. This paper presents an algorithm to utilize the activity measurement by DC value and the number of non-zero quantized DCT coefficients in the residual macroblock to compose the motion vector. It can reduce the complexity for motion estimation and improve the performance of the spatial domain video transcoder.

The newest video coding standard called H.264 provides considerable performance improvement over a wide range of bit rates and video resolutions compared to previous standards. However, these features result in an extraordinary increase in encoder complexity, mainly regarding to mode decision and multiple reference frame motion estimation (ME). This letter presents two algorithms to reduce the computational complexity caused by motion estimation. The adaptive search range decision method determines the search range size according to the motion vector predictor dynamically and the early termination scheme defines a criterion to early terminate the search processing for multiple reference frames. Experimental results show that the proposed algorithms provide significant improvement of coding speed with negligible objective quality degradation compared to the fast motion estimation algorithms adopted by reference software.

The deblocking filter in H.264 is an efficient tool to reduce blocking artifact, but it also blurs the details or retains blocking artifact perceptible in some high-activity areas. In this paper, we improve the filtered pixel classification and filtering schemes used by the deblocking filter in H.264 to keep the sharpeness of real edges and minimize over-smoothing.

Compressed video bitstream is sensitive to errors that may degrade the reconstructed images severely even the bit error rate is small. One approach to combat the impact of error is error concealment at the decoder without increasing the bit rate and changing the encoder. We propose motion vector based error concealment algorithms to recover the motion vector per pixel instead of that per block according to the relation of neighboring motion vectors. The displacement per pixel can be estimated more accurately by using the tendency of neighboring motion vectors. Besides, we use not only the relation among motion vectors, but also the pixels. The pixels of the error block are divided into different parts according to their consistency with neighboring blocks and the displacement at each pixel of these parts is interpolated by relative motion vectors. From simulation results, the proposed motion vector based methods provide better reconstruction quality for damaged images than other methods.

The three main reasons why the new H.264 (MPEG-4 AVC) video coding standard has a significant performance better than the other standards are the adoption of variable block sizes, multiple reference frames, and the consideration of rate distortion optimization within the codec. However, these features incur a considerable increase in encoder complexity. As for the multiple reference frames motion estimation, the increased computation is in proportion to the number of searched reference frames. In this paper, a fast multi-frame selection method is proposed for H.264 video coding. The proposed scheme can efficiently determine the best reference frame from the allowed five reference frames. Simulation results show that the speed of the proposed method is over two times faster than that of the original scheme adopted in JVT reference software JM73 while keeping the similar video quality and bit-rate.

This paper proposes a fast motion estimation algorithm for variable block-sizes by utilizing motion vector bottom-up procedure for H.264. The refined motion vectors of adjacent small blocks are merged to predict the motion vectors of larger blocks for reducing the computation. Experimental results show that our proposed method has lower computational complexity than full search, fast full search and fast motion estimation of the H.264 reference software JM93 with slight quality decrease and little bit-rate increase.

Location sharing services have recently gained momentum over mobile online social networks (mOSNs), seeing the increasing popularity of GPS-capable mobile devices such as smart phones. Despite the convenience brought by location sharing, there comes severe privacy risks. Though many efforts have been made to protect user privacy during location sharing, many of them rely on the extensive deployment of trusted Cellular Towers (CTs) and some incur excessive time overhead. More importantly, little research so far can support complete privacy including location privacy, identity privacy and social relation privacy. We propose SAM, a new System Architecture for mOSNs, and P3S, a Privacy-Preserving Protocol based on SAM, to address the above issues for privacy-preserving location sharing over mOSNs. SAM and P3S differ from previous work in providing complete privacy for location sharing services over mOSNs. Theoretical analysis and extensive experimental results demonstrate the feasibility and efficiency of the proposed system and protocol.