MPEG is currently developing a new scalable video coding (SVC) standard which should provide compression efficiency similar to current non-scalable video coding standard. The extension of H.264/AVC hybrid video coding using motion-compensated temporal filtering (MCTF) is a current solution. This paper presents a dynamic group of picture (GOP) structure to improve the quality of the SVC coded video by using variable GOP sizes along the video sequences without the restriction of the fixed GOP size or the limited adaptive GOP size. The dynamic GOP structure keeps temporal importance information of frames in the encoded video, which helps in coding efficiency and provides better user perception. An effective GOP size determination method is also proposed in this paper. The proposed scheme has been validated by experimental results.
KEYWORDS: Computer programming, Video, Video processing, Cameras, Visualization, Video compression, Video coding, Image visualization, Image quality, Internet
The progress of data transmission technology through the Internet has spread a variety of realistic contents. One of
such contents is multi-view video that is acquired from multiple camera sensors. In general, the multi-view video
processing requires encoders and decoders as many as the number of cameras, and thus the processing complexity
results in difficulties of practical implementation.
To solve for this problem, this paper considers a simple multi-view system utilizing a single encoder and a single
decoder. In the encoder side, input multi-view YUV sequences are combined on GOP units by a video mixer. Then, the
mixed sequence is compressed by an H.264/AVC encoder. The decoding is composed of a single decoder and a
scheduler controlling the decoding process. The goal of the scheduler is to assign approximately identical number of
decoded frames to each view sequence by estimating the decoder utilization of a GOP and subsequently applying frame
skip algorithms. Furthermore, in the frame skip, efficient frame selection algorithms are studied for H.264/AVC
baseline and main profiles based upon a cost function that is related to perceived video quality.
Our proposed method has been performed on various multi-view test sequences adopted by MPEG 3DAV.
Experimental results show that approximately identical decoder utilization is achieved for each view sequence so that
each view sequence is fairly displayed. Finally, the performance of the proposed method is compared with a simulcast
encoder in terms of bit-rate and PSNR using a rate-distortion curve.
Given the small bit allocation for motion information in very low bit-rate coding, motion estimation using the block matching algorithm (BMA) fails to maintain an acceptable level of prediction errors. The reason is that the motion model, or spatial transformation, assumed in block matching cannot approximate the motion in the real world precisely with a small number of parameters. In order to overcome the drawback of the conventional block matching algorithm, several triangle-based methods which utilize triangular patches instead of blocks have been proposed. To estimate the motions of image sequences, these methods usually have been based on the combination of optical flow equation, affine transform, and iteration. But the computational cost of these methods is expensive. This paper presents a fast motion estimation algorithm suing a multiple linear regression model to solve the defects of the BMA and the triangle-based methods. After describing the basic 2D triangle-based method, the details of the proposed multiple linear regression model are presented along with the motion estimation results from one standard video sequence, representative of MPEG-4 class A data. The simulation results show that in the proposed method, the average PSNR is improved about 1.24 dB in comparison with the BMA method, and the computational cost is reduced about 40 percent in comparison with the 2D triangle-based method.
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