Conventional Rate Control (RC) schemes for video coding mostly take objective metric as distortion measurement, which can not achieve optimal subjective quality. This work applies Structural Similarity (SSIM) based su...
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H.264/AVC adopts rate distortion optimization (RDO) technique to select optimal macroblock (MB) coding mode and achieves higher compression efficiency, but the traditional RDO framework employs pixelwise mean square e...
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Conventional Rate Control (RC) schemes for video coding mostly take objective metric as distortion measurement, which can not achieve optimal subjective quality. This work applies Structural Similarity (SSIM) based su...
详细信息
Conventional Rate Control (RC) schemes for video coding mostly take objective metric as distortion measurement, which can not achieve optimal subjective quality. This work applies Structural Similarity (SSIM) based subjective distortion to rate distortion optimization and RC in H.264, and proposes a SSIM optimal macroblock (MB) layer RC scheme. First, a SSIM quadratic distortion model is proposed based on extensive experiments and theoretical analysis. Then an improved quadratic Rate Quantization (R-Q) model is combined to obtain the solution of SSIM optimal MB layer quantization step (Qstep) by Lagrange multiplier method. Experimental results show that the proposed scheme preserves more image structural information and thus acquires better subjective quality compared with objective metric optimal MB layer RC JVT-O016 and classic JVT-G012.
This paper proposes a robust piecewise planar multiview stereo (MVS) approach specifically designed for urban scenes. These architectural scenes are problematic for traditional computer vision methods. In our work, we...
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Rate control is one of the key factors influencing the multi-view video ***,there is not a rate control algorithm in the existing Joint Multi-view Video Coding *** this paper,an efficient rate control algorithm and a ...
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Rate control is one of the key factors influencing the multi-view video ***,there is not a rate control algorithm in the existing Joint Multi-view Video Coding *** this paper,an efficient rate control algorithm and a bit allocation strategy for multi-view video coding are *** order to obtain the consistent view quality,a bit allocation model based on the Lagrange optimum algorithm is firstly ***,considering the encoding statistical characteristics of different view types,a view weighting factor is introduced,and it will help improve the precision of bit allocation among *** with the fixed QP control strategy,experiment results show that the proposed algorithm can efficiently control the bit rate and obtain more consistent views,with video visual quality improved.
Camera calibration is the essential step of obtaining 3D information from 2D views in the field of computer vision, which is widely used in the area of 3D reconstruction, navigation, visual supervision, etc. A camera ...
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H.264/AVC adopts rate distortion optimization (RDO) technique to select optimal macro block (MB) coding mode and achieves higher compression efficiency, but the traditional RDO framework employs pixel wise mean square...
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H.264/AVC adopts rate distortion optimization (RDO) technique to select optimal macro block (MB) coding mode and achieves higher compression efficiency, but the traditional RDO framework employs pixel wise mean square error (MSE) and the like as objective distortion metric, which can not acquire optimal subjective quality. This paper applies structural similarity (SSIM) based subjective distortion to RDO-based intra mode decision in H.264 I frame coding, and further proposes a frame layer adaptive Lagrange multiplier adjustment scheme to get better tradeoff between rate and SSIM distortion. Experimental results show that, the proposed scheme encodes more image structural information and thus acquires better subjective quality and coding efficiency compared with MSE-based RDO method.
When wireless hosts use different rates to transmit data in IEEE 802.11 networks, it will take on the state of performance anomaly which will severely decrease the throughputs of all the higher rate hosts. Hence, it i...
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When wireless hosts use different rates to transmit data in IEEE 802.11 networks, it will take on the state of performance anomaly which will severely decrease the throughputs of all the higher rate hosts. Hence, it is bad for video service transmission. Considering that video is very sensitive to packet delivery delay but can tolerate some packet losses, we propose a novel cross-layer scheme which takes these two characteristics into consideration. Firstly, the maximum number of retransmissions for a video Medium Access Control (MAC) frame is computed in MAC layer according to video frame rate requirement of application layer and current access delay of MAC layer. Secondly, within the margin of the tolerant Packet Loss Rate (PLR) of application layer, several video MAC frames are allowed to drop so that we can adaptively select the transmission rate as high as possible for the rest of video MAC frames in terms of current channel quality and the maximum number of retransmissions. Experiment results show that the proposed method can reduce the delay and jitter of video service and improve the throughputs of fast hosts. Therefore, it increases the quality of reconstructed video to a certain extent and relieves the performance anomaly of network effectively.
This paper proposes a robust piecewise planar multi view stereo (MVS) approach specifically designed for urban scenes. These architectural scenes are problematic for traditional computer vision methods. In our work, w...
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This paper proposes a robust piecewise planar multi view stereo (MVS) approach specifically designed for urban scenes. These architectural scenes are problematic for traditional computer vision methods. In our work, we focus on exploiting some useful constraints of artificial structures such as piecewise coplanarity and boundaries of superpixels. Firstly, we reconstruct quasi-dense 3D point clouds of urban scenes using patches-based MVS (PMVS) method. Secondly, a set of 3D candidate planes are generated by the obtained point clouds without any assumption on the normals of planes, unlike famous Manhattan-world assumption. Then, we segment multi-view images with watershed algorithm and modify the contours of superpixels by the classical Douglas-Peucker approximation algorithm to fit the contours to the boundaries of objects in urban scenes as much as possible. Finally, we use the candidate planes as labels and superpixels as nodes to formulate our Markov Random Field (MRF) optimization problem, then a piecewise planar depth map for each view is recovered by solving the optimization problem using graph-cuts. Experiments show that our method outperforms previous approaches in terms of accuracy.
This letter presents a novel Motion Vector (MV) recovery method which is based on Mean Shift (MS) procedure. According to motion continuity, MVs in local area should be similar. If projecting MV into 2-D feature space...
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This letter presents a novel Motion Vector (MV) recovery method which is based on Mean Shift (MS) procedure. According to motion continuity, MVs in local area should be similar. If projecting MV into 2-D feature space, local MVs in the feature space tend to cluster closely. To estimate the lost MVs in local area, recovery of lost MVs is modeled as clustering operation. MS procedure is applied to enforce each lost MV in the feature space to shift to the position where dominant MVs are gathered. Meanwhile, bandwidth estimation is statistically characterized by the variation of local standard de-viations; weighted value calculation is determined by estimation of overall standard deviation. Simu-lation results demonstrate their better performance when compared with other MV recovery ap-proaches and low computation cost.
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