We propose in this paper a novel error resilient transcoding scheme that can be placed at the boundary between wired and wireless networks via heterogeneous network links. This error resilient transcoder shall seamlessly complement the standard Scalable Video Coding (SVC) bitstream to offer additional error resilient adaptation capability for receiving devices. The novel error resilient transcoding scheme consists of three different modules; each is designed to meet various levels of complexity need. The three modules are all based on the Loss-Aware Rate-Distortion Optimization (LA-RDO) mode decision algorithm we have previously developed for SVC. However, each individual module can be tailored to different complexity requirements depending on whether and how the LA-RDO mode decision is implemented. Another innovation of this approach is the design of a fast rate control algorithm in order to maintain consistent bitrates between input and output of the transcoder. This rate control algorithm only needs picture-level bit information for training target quantization parameters. Simulation results demonstrate that, comparing with standard SVC, the proposed approach is able to achieve up to 4 dB gain for the enhancement layer video and up to 1 dB gain for the base layer video.

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.

The Multiview Video Coding (MVC) standard is currently under development by the Joint Video Team as an extension of the Advanced Video Coding (H.264/AVC) standard. An MVC encoder compresses more than one viewpoint of a scene captured by different cameras. Redundancies between views can be used for inter-view prediction in encoding as well as error concealment in decoding. In this paper, a new algorithm utilizing motion information of pictures from other views to conceal a lost picture is proposed. The algorithm first derives motion information for a lost picture based on motion fields of pictures in adjacent views. Then, traditional motion compensation is invoked within the view containing the lost picture to derive a concealed frame. Experimental results show that the proposed algorithm can improve video quality with a negligible computational complexity overhead compared to simple temporal error concealment algorithms.

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.

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.