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Resolution-independent Up-sampling for Depth Map Using Fractal Transforms
( Meiqin Liu ),( Yao Zhao ),( Chunyu Lin ),( Huihui Bai ),( Chao Yao ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.6
Due to the limitation of the bandwidth resource and capture resolution of depth cameras, low resolution depth maps should be up-sampled to high resolution so that they can correspond to their texture images. In this paper, a novel depth map up-sampling algorithm is proposed by exploiting the fractal internal self-referential feature. Fractal parameters which are extracted from a depth map, describe the internal self-referential feature of the depth map, do not introduce inherent scale and just retain the relational information of the depth map, i.e., fractal transforms provide a resolution-independent description for depth maps and could up-sample depth maps to an arbitrary high resolution. Then, an enhancement method is also proposed to further improve the performance of the up-sampled depth map. The experimental results demonstrate that better quality of synthesized views is achieved both on objective and subjective performance. Most important of all, arbitrary resolution depth maps can be obtained with the aid of the proposed scheme.
Sensorless Control of PMSG for A Wind Power System Based on CSC
MAO Meiqin,LIU Fuyan,MU Junsheng,XU Bin 전력전자학회 2011 ICPE(ISPE)논문집 Vol.2011 No.5
This paper presents sensorless rotor-flux-oriented control algorithms for the PMSG used in the direct drive wind generation system with a back-to-back current source converter. The proposed algorithms are based on phase-lock-loop and model reference adaptive system methods. These algorithms are analyzed, compared and verified by the simulation and experiment. The simulation and experiment results show that the PLL method is simpler, but more accurate, and has a faster dynamic performance than MRAS method.
Optimized Multiple Description Lattice Vector Quantization Coding for 3D Depth Image
( Huiwen Zhang ),( Huihui Bai ),( Yao Zhao ),( Meiqin Liu ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.3
Multiple Description (MD) coding is a promising alternative for the robust transmission of information over error-prone channels. Lattice vector quantization (LVQ) is a significant version of MD techniques to design an MD image coder. However, different from the traditional 2D texture image, the 3D depth image has its own special characteristics, which should be taken into account for efficient compression. In this paper, an optimized MDLVQ scheme is proposed in view of the characteristics of 3D depth image. First, due to the sparsity of depth image, the image blocks can be classified into edge blocks and smooth blocks, which are encoded by different modes. Furthermore, according to the boundary contents in edge blocks, the step size of LVQ can be regulated adaptively for each block. Experimental results validate the effectiveness of the proposed scheme, which show better rate distortion performance compared with the conventional MDLVQ.