This paper presents a comparison between the scalable extension of H.264/AVC (SVC) and transcoding, in terms of Rate-Distortion(RD) performance and computational complexity. Both bitrate and spatial resolution reduction cases are included. Simulation results show that, in the aspect of RD performance, SVC performs significantly better in bitrate reduction and slightly better in spatial resolution reduction. Meanwhile, SVC adaptation through bitstream extraction has negligible complexity compared with transcoding1.

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.

This paper presents several error resilient video coding methods based on redundant pictures. We combine redundant picture coding with reference picture selection and reference picture list reordering to prevent error propagation in motion compensated video coding. A hierarchical redundant picture allocation method is employed to make a tradeoff between error resilience and coding efficiency. For improved end-to-end rate-distortion performance in packet loss environment, three adaptive redundant picture allocation methods are further developed, utilizing characteristics of the input video content. Simulation results show that the adaptive redundant picture coding methods can achieve average luma peak-signal-to-noise improvements up to 3.5 dB compared to the loss-aware rate distortion optimized intra macroblock refresh algorithm implemented in the H.264/AVC Joint Model (JM). The proposed redundant picture coding methods are standard-compliant and do not introduce any additional end-to-end delay, therefore suit for low-delay applications such as video telephony and video conferencing. Due to the good error resilience performance, some of the proposed redundant picture coding methods have been adopted and integrated into the JM.

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.

Recently, image-based, high throughput RNA interference (RNAi) experiments are increasingly carried out to facilitate the understanding of gene functions in intricate biological processes. Effective automated segmentation technique is significant in analysis of RNAi images. However, graph cuts based active contour (GCBAC) method needs interaction during segmentation. Here, we present a novel approach to overcome this shortcoming. The process consists the following steps: First, region-growing algorithm uses extracted nuclei to get the initial contours for segmentation of cytoplasm. Then, constraint factor obtained from binary segmentation of enhanced image is incorporated to improve the performance of cytoplasm segmentation. Finally, morphological thinning algorithm is implemented to solve the touching problem of clustered cells. Our approach can automatically segment clustered cells with polynomial time-consuming. The excellent results verify the effectiveness of the proposed approach.