Scalable video coding (SVC), which is the scalable extension of the H.264/AVC standard, was developed by the Joint Video Team (JVT) of ISO/IEC MPEG (Moving Picture Experts Group) and ITU-T VCEG (Video Coding Experts Group). SVC is designed to provide adaptation capability for heterogeneous network structures and different receiving devices with the help of temporal, spatial, and quality scalabilities. It is challenging to achieve graceful quality degradation in an error-prone environment, since channel errors can drastically deteriorate the quality of the video. Error resilient coding and error concealment techniques have been introduced into SVC to reduce the quality degradation impact of transmission errors. Some of the techniques are inherited from or applicable also to H.264/AVC, while some of them take advantage of the SVC coding structure and coding tools. In this paper, the error resilient coding and error concealment tools in SVC are first reviewed. Then, several important tools such as loss-aware rate-distortion optimized macroblock mode decision algorithm and error concealment methods in SVC are discussed and experimental results are provided to show the benefits from them. The results demonstrate that PSNR gains can be achieved for the conventional inter prediction (IPPP) coding structure or the hierarchical bi-predictive (B) picture coding structure with large group of pictures size, for all the tested sequences and under various combinations of packet loss rates, compared with the basic Joint Scalable Video Model (JSVM) design applying no error resilient tools at the encoder and only picture copy error concealment method at the decoder.

Abstract—We present a novel 2-D wavelet transform scheme of adaptive directional lifting (ADL) in image coding. Instead of alternately applying horizontal and vertical lifting, as in present practice, ADL performs lifting-based prediction in local windows in the direction of high pixel correlation. Hence, it adapts far better to the image orientation features in local windows. The ADL transform is achieved by existing 1-D wavelets and is seamlessly integrated into the global wavelet transform. The predicting and updating signals of ADL can be derived even at the fractional pixel precision level to achieve high directional resolution, while still maintaining perfect reconstruction. To enhance the ADL performance, a rate-distortion optimized directional segmentation scheme is also proposed to form and code a hierarchical image partition adapting to local features. Experimental results show that the proposed ADL-based image coding technique outperforms JPEG 2000 in both PSNR and visual quality, with the improvement up to 2.0 dB on images with rich orientation features.

Multiview video coding (MVC) is currently under development by the Joint Video Team (JVT) as an extension to Advanced Video Coding (H264/AVC). Based on the suppression theory in binocular vision, the fidelity of one of the two views of a stereoscopic display can be reduced without noticeable degradation of subjective quality. Thus, in MVC, a subset of views can be coded with lower spatial resolution at negligible cost to subjective quality. Due to different resolutions, a downsampling process is required in an MVC decoder in order to enable motion compensation (MC) between views. In this paper, a low-complexity MC algorithm is proposed for MVC to enable inter-view prediction between pictures with different resolutions. It requires lower memory consumption and lower computational complexity compared with the conventional downsampled inter-view prediction, while providing comparable efficiency, as shown by the simulation results.

This paper proposes a video coding scheme, in which textural and structural regions are selectively removed in the encoder, and restored in the decoder by spatio-temporal texture synthesis and edge-based inpainting. In the proposed scheme, two types of regions are classified based on two motion models: local motion and global motion. In local motion regions, conventional blockbased motion estimation is employed for region removal and spatio-temporal texture synthesis is applied for recovery of the removed regions. In global motion regions, edge-based image inpainting is utilized to recover removed regions, and sprite generation is used as an auxiliary tool to keep temporal consistency. In the proposed scheme, both structures and textures are handled and some kinds of assistant information which can guide restoration are extracted and coded. This approach is blockbased and thus is flexible and generic to be implemented into standard-compliant video coding schemes. It has been implemented into H.264/AVC and achieves up to 35% bitrate saving at similar visual quality levels compared with H.264/AVC without our approach.

3D facial extraction from volume data is very helpful in virtual plastic surgery. Although the traditional Marching Cubes algorithm (MC) can be used for this purpose, it could not separate the facial surface from other tissue surfaces. This weakness greatly limited the accuracy of the facial model and its application in plastic surgery. In this paper a volume graph model is proposed, in which the facial surface extraction is formulated as a min-cut problem and can be solved by existing graph cut algorithm. Based on this model, irrelevant tissue surfaces are effectively excluded and a more accurate 3D virtual face can be built for plastic surgery.