Linjian Mo

A novel fast predictive mode decision algorithm for H.264

H.264 video coding standard achieves significant improvement on coding efficiency due to its variable-block-size motion estimation (ME). However, it also leads to much higher computational complexity. This paper presents a novel fast predictive mode decision algorithm to accelerate the ME process for H.264 encoder. Firstly, an earlytermination mechanism is introduced to determine the stationary and motion-followed macroblocks (several surrounding blocks have identical motion vectors (MVs)) with adaptive threshold. Secondly, in order to predict the MVs of up-layer blocks, we apply a fast predictive MV search on the 4x4 blocks in non-determined macroblocks which are not early-determined in step 1. Finally, with these predictive MVs, a bottom-up merging method is performed to finish mode decision procedure. Experimental results show that our proposed algorithm can reduce the encoding computational complexity to about 70% of JM8.5 encoder, with negligible average PSNR drop and small bitrate increase.

Multiframe Error Concealment for Whole-Frame Loss in H.264/AVC

In this paper, we propose a novel error concealment algorithm for the whole-frame loss based on multiframe. In concealing procedure, besides improve the quality of the concealed lost frames, the proposed algorithm also guarantees the quality of the succeeding frames that reference the lost frame in order to control the propagation of errors. Macroblocks in the lost frame are concealed in an appropriate order which is determined by exploiting the information from partly decoded succeeding frames. Experimental results demonstrate that the proposed algorithm not only outperforms previous algorithms in both PSNR evaluation and visual quality of the concealed lost frames, but also minimizes the error propagation.

A Novel Fast Error-resilient Video Coding Scheme for H.264

Both perceptually and statistically, compressed video with large or disordered motion is sensitive to errors. In this paper, we propose a novel fast error-resilient video coding scheme, which is based on significant macroblock (MB) determination and protection. The scheme takes three impact factors (inter-block mode, motion vector difference and SAD value) to build a statistical model. The model takes error concealment (EC) into consideration in advance and generates several parameters for further significant degree (SD) evaluation for MBs. During encoding, we build an SD table for each frame based on the parameters and pick up those MBs with the largest SD values as significant MBs (SMBs). Few additional computations are induced into SMB determination, thus make our scheme practical in real time video coding scenarios. Simulations show that the scheme has an acceptable SMB determination accuracy and the corresponding protection method can prevent errors effectively

Configurable complexity-bounded motion estimation for real-time video encoding

Motion estimation (ME) is by far the main bottleneck in real-time video coding applications. In this paper, a configurable complexity-bounded motion estimation (CCBME) algorithm is presented. This algorithm is based on prediction-refinement techniques, which make use of spatial correlation to predict the search center and then use local refinement search to obtain the final motion field. During the search process, the ME complexity is ensured bounded through three configuration schemes: 1) configure the number of predictors; 2) configure the search range of local refinement; 3) configure the subset pattern of matching criterion computation. Different configuration leads to different distortion. Through joint optimization, we obtain a near-optimal complexity-distortion (C-D) curve. Based on the C-D curve, we preserve 6 effective configurable modes to realize the complexity scalability, which can achieve a good tradeoff between ME accuracy and complexity. Experimental results have shown that our proposed CCBME exhibits higher efficiency than some well-known ME algorithms when applied on a wide set of video sequences. At the same time, it possesses the configurable complexity-bounded feature, which can adapt to various devices with a wide range of computational capability for real-time video coding applications.

Complexity reduction of multi-frame motion estimation in h.264

H.264 video coding standard gains significant improvement in compression efficiency. However, the computational complexity also considerably increases. Many fast algorithms are introduced to speed up the encoding. Distinguishing from pervious multi-frame based fast motion estimation algorithms which only exploit temporal correlation, a novel algorithm both employing temporal and spatial correlations is proposed in this paper, which has much better prediction accuracy. To further speed up the encoding process, an adaptive mode reduction scheme which will discard small probability modes is also proposed. Combining the novel fast multi-frame based motion estimation algorithm and the adaptive mode reduction scheme, experimental results show that the proposed algorithms improve the encoding speed by an average of 9 times faster than fast full search and about 2.5 times faster than reference method which only employs temporal correlation, PSNR dropping and bitrate increasing are negligible.

Rate control scheme for video coding using low-memory-cost look-up table

This paper presents a new MPEG-4/H.263 rate control scheme. It is applicable to constant-bit-rate transmissions containing equal-interval I-frames. Conventional schemes usually allocate bits equally to each P-frame, resulting in large video quality variations. In this work, in order to smooth quality variations, we allocate bits unequally to each P-frame by its encoding complexity and buffer level. In macroblock (MB) layer, rate-distortion model is usually employed to determine MB QP, but it needs complex floating-point computations. So, instead, we design a simple and effective look-up table, which also relates MB QP, SAD and the texture bit counts. With certain improvements, our table size reduces to only 1/20 of that in reference work, while the scheme still performs well. Experimental results show that, compared with a modified TMN8 rate control scheme, our scheme achieves higher PSNR and smoother PSNR variations, retaining the bit rate proximity and buffer regulation.

Multiple-Reference-Frame Based Fast Motion Estimation & Mode Decision for H.263-to-H.264 Transcoder

To-H.264 transcoding, due to its high practical values for a wide range of realtime video applications, has become an active research topic. However, most of the previous works do not address a very important new feature of H.264, multiple-reference-frame motion estimation. In this paper, employing forward domain vector selection (FDVS) and top-down splitting algorithms, a novel fast multiple-reference-frame based motion estimation & mode decision algorithm for H.263-to-H.264 transcoder is proposed. Potential block-sizes reduction and early-stop strategies are also adopted to accelerate the processing. Moreover, a novel adaptive search range selection algorithm is proposed to further speed up the motion search while the coding efficiency is not compromised. Proposed algorithm can also be extended to support transcoding other format videos to H.264, such as MPEG2-to-H.264. Experimental results show that the computational complexity can be reduced to about 11% of reference transcoder with negligible PSNR drop and a little bit-rate increase.

Multiple description coding using adaptive error recovery for real-time video transmission

Real-time video transmission over packet networks faces several challenges such as limited bandwidth and packet loss. Multiple description coding (MDC) is an efficient error-resilient tool to combat the problem of packet loss. The main problem of MDC is the mismatch of reference frames in encoder and decoder, when some descriptions are lost during transmission. This paper presents an adaptive error recovery (AER) scheme for multiple description video coding. The proposed AER scheme, which is based on statistical analysis, can adaptively determine the nearly optimal error recovery (ER) method among our predefined ER methods such as interpolation, block replacement and motion vector (MV) reusing. The AER scheme has three advantages. First, it efficiently reduces the mismatch error. Second, it is completely based on pre- post-processing which requires no modification of the source coder. Third, it has low computational complexity, which is suitable for real-time video applications. Simulation results demonstrate that our proposed AER scheme achieves better performance compared with MDC with fixed error recovery (FER) scheme over lossy networks.

Speed optimization of a MPEG-4 software decoder based on ARM family cores

MPEG-4 visual simple profile is a widely used video compression standard for mobile solutions. In general, MPEG-4 video decoder requires high computation power for its complex algorithms. Its difficult to implement MPEG-4 video decoder on hand-held devices directly. In this paper, we proposed a novel color space transform algorithm and optimized the memory access operations. Moreover, the multiperless integer IDCT is adopted to further speed up the decoder. Our optimization is based on ARM7TDMI and ARM920T, which are very desirable cores to mobile solutions for low power consumption. Experimental results show that the optimized decoder acts about 5 times faster than existing XVID MPEG-4 video decoder with small video quality degradation and supports real-time video applications.