A method of decoding a video signal is disclosed. The present invention includes obtaining identification information indicating whether a coded picture of a current NAL unit is an inter-view picture group, obtaining interview reference information of the inter-view picture group, and constructing a reference picture list for inter-view prediction using the inter-view reference information according to the identification information, wherein the inter-view reference information includes view identification information of an inter-view reference picture.

Method and apparatus for decoding/encoding a video signal

A method comprises receiving a first sequence of access units and a second sequence of access units; decoding at least one access unit of the first sequence of access units; decoding a first decodable access unit of the second sequence of access units; determining whether a next decodable access unit in the second sequence of access units can be decoded before an output time of the next decodable access unit in the second sequence of access units; and skipping decoding of the next decodable access unit based on determining that the next decodable access unit cannot be decoded before the at least one of the decoding time and the output time of the next decodable access unit.

Method and apparatus for video coding and decoding

A modular intelligent transportation system, comprising an environmentally protected enclosure, a system communications bus, a processor module, communicating with said bus, having a image data input and an audio input, the processor module analyzing the image data and/or audio input for data patterns represented therein, having at least one available option slot, a power supply, and a communication link for external communications, in which at least one available option slot can be occupied by a wireless local area network access point, having a communications path between said communications link and said wireless access point, or other modular components.

Modular intelligent transportation system

Rate control is a useful tool for video coding, especially in real-time communication applications. Most of existing rate control algorithms are based on the R-Q model, which characterizes the relationship between bitrate R and quantization Q , under the assumption that Q is the critical factor on rate control. However, with the video coding schemes becoming more and more flexible, it is very difficult to accurately model the R-Q relationship. In fact, we find that there exists a more robust correspondence between R and the Lagrange multiplier λ . Therefore, in this paper, we propose a novel λ -domain rate control algorithm based on the R-λ model, and implement it in the newest video coding standard high efficiency video coding (HEVC). Experimental results show that the proposed λ -domain rate control can achieve the target bitrates more accurately than the original rate control algorithm in the HEVC reference software as well as obtain significant R-D performance gain. Thanks to the high accurate rate control algorithm, hierarchical bit allocation can be enabled in the implemented video coding scheme, which can bring additional R-D performance gain. Experimental results demonstrate that the proposed λ -domain rate control algorithm is effective for HEVC, which outperforms the R-Q model based rate control in HM-8.0 (HEVC reference software) by 0.55 dB on average and up to 1.81 dB for low delay coding structure, and 1.08 dB on average and up to 3.77 dB for random access coding structure. The proposed λ -domain rate control algorithm has already been adopted by Joint Collaborative Team on Video Coding and integrated into the HEVC reference software.

λ domain rate control algorithm for high efficiency video coding.

The present invention relates to a method for conducting interlayer motion prediction in encoding or decoding of video signal. The present method sets motion information of an intra-mode macro block of a base layer with motion information of an inter-mode macro block that is vertically adjacent to the intra-mode macro block, derives motion information of a pair of macro blocks adjacent vertically each other from the two macro blocks, and uses the pair of macro blocks in inter-layer motion prediction.

Inter-Layer Prediction Method for Video Signal

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.

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Error Resilient Coding and Error Concealment in Scalable Video Coding

Error resilient macroblock mode decision has been extensively investigated in the literature for single-layer video coding, for which error resilient mode decision is also called as intra refresh. In this paper, we present a loss-aware rate-distortion optimized macroblock mode decision algorithm for scalable video coding, wherein more macroblock coding modes than intra and inter are involved. Thanks to the good performance, the proposed method has been adopted into the joint scalable video model by the joint video team.

Error Resilient Mode Decision in Scalable Video Coding

Template matching intra prediction has been reported earlier, to generate intra prediction signal from wider reconstructed areas compared with H.264/AVC intra prediction. In this paper an improved intra prediction scheme which introduces priority-guided template matching is presented. The proposed method first calculates a priority value of each pixel on the border between the current to-be-predicted block and the reconstructed or predicted area, and then performs template matching for the template centered on the pixel with the highest priority among all the border pixels, in an iterative manner. Simulation results demonstrate that the proposed algorithm can save about 2% bitrate than the non-priority algorithm.

Priority-based template matching intra prediction

A system and method for improving both coding efficiency and decoding accuracy in scalable video coding involving discardable lower layer adaptations, where applications can omit transmission of unused data for inter-layer prediction for all layers below an operation point of receivers. Indicator flags are utilized to avoid transmitting syntax elements that must be set to fixed values. In addition, padding algorithms or additional encoding constraints are applied to the encoding process.

Discardable lower layer adaptations in scalable video coding

In this paper, we present a novel low complexity yet very efficient rate control algorithm for Scalable Video Coding (SVC) based on the ρ-domain model. Compared with the conventional ρ-domain model in determining quantization parameter, the proposed algorithm adopts a new linear model to obtain the quantization parameter at frame-level. This linear model is able to characterize the relationship between the percentage of zero among quantized coefficients and the quantization step. Since this model considers the Mean Absolute Difference (MAD) of each frame, individual frame only needs to be encoded once to control the bit-rate. In particular, the model parameter in the ρ-domain model can be adaptively estimated by utilizing either temporal or inter-layer information. This leads to significant improvement in estimation accuracy. Experimental results show that the proposed algorithm can achieve accurate bit-rate and maintain the maximum mismatch between actual bit-rate and target bit-rate within 0.5%. More importantly, the proposed low complexity algorithm is able to obtain PSNR improvement up to 0.6dB comparing with the algorithm adopted in the Joint Scalable Video Model (JSVM).

Yi Guo

Papers

Error Resilient Coding and Error Concealment in Scalable Video Coding

Error Resilient Mode Decision in Scalable Video Coding

Priority-based template matching intra prediction

Discardable lower layer adaptations in scalable video coding

Low-complexity rate control based on ρ-domain model for Scalable Video Coding