Oscar C. Au

Predictive motion vector field adaptive search technique (PMVFAST): enhancing block-based motion estimation

Motion Estimation (ME) is an important part of most video encoding systems, since it could significantly affect the output quality of an encoded sequence. Unfortunately this feature requires a significant part of the encoding time especially when using the straightforward Full Search (FS) algorithm. In this paper a new algorithm is presented named as the Predictive Motion Vector Field Adaptive Search Technique (PMVFAST), which significantly outperforms most if not all other previously proposed algorithms in terms of Speed Up performance. In addition, the output quality of the encoded sequence in terms of PSNR is similar to that of the Full Search algorithm. The proposed algorithm relies mainly upon very robust and reliable predictive techniques and early termination criteria, which make use of parameters adapted to the local characteristics of a frame. Our experiments verify the superiority of the proposed algorithm, not only versus several other well-known fast algorithms, but also in many cases versus even the Full Search algorithm.

New results on zonal based motion estimation algorithms-advanced predictive diamond zonal search

Zonal based motion estimation algorithms have been gaining in popularity in video coding. This is due to their superior performance and reduced complexity versus other conventional algorithms. In this paper we propose a further improvement on these algorithms named the Advanced Predictive Diamond Zonal Search (APDZS). The proposed algorithm introduces the concepts of multiple initial predictor candidates and adaptive thresholding, and manages to significantly improve the reliability and performance of the estimation. Extensive simulation results demonstrate that the performance of this algorithm is equivalent in terms of PSNR, to that of the brute force full search algorithm even for the most complicated sequences, with almost negligible complexity.

A novel approach to fast multi-block motion estimation for H.264 video coding

The upcoming video coding standard, H.264, uses motion estimation with multiple block sizes to improve the rate-distortion performance. However, full exhaustive search of all block sizes is computational intensive with complexity increasing linearly with the number of allowed block size. In this paper, a novel fast multi-block motion estimation (FMBME) is proposed for H.264 video coding. Experimental results show that the proposed FMBME can efficiently reduce the computational cost by 40.73% with similar visual quality and bit rate.

Fast motion estimation using modified circular zonal search

In this paper we present a new fast motion estimation method used in video coding. It is shown that the new algorithm is not only much faster than traditional algorithms, but in some cases can achieve much better visual quality, even from the optimal but computationally intensive full search algorithm.

Enhanced predictive motion vector field adaptive search technique (E-PMVFAST)-based on future MV prediction

Motion estimation (ME) is a core part of most modern video coding standard, and it directly affects the compression efficiency and visual quality of a video. If full search (FS) algorithm is used, ME could takes over 70% of computational power. Many algorithms such as TSS and PMVFAST, have been developed to achieve great speed up for ME. In this paper, a new algorithm enhanced-PMVFAST (E-PMVFAST) is proposed, which performs better than most if not all other existing algorithms in terms of speed up factor while keeping the similar PSNR with FS. Our experiments have also verified the robustness of the proposed E-PMVFAST algorithm.

New predictive diamond search algorithm for block-based motion estimation

In this paper a new fast motion estimation algorithm is presented. The algorithm, named as Predictive Diamond Search, is actually based on the Diamond Search (DS) algorithm, which was recently adopted inside the MPEG-4 standard. The DS algorithm, even though faster than most known algorithms, was found not to be very robust in terms of quality for several sequences. By introducing a new predictive criterion and some additional steps in DS, our simulation results show that the proposed algorithm manages to have similar complexity with the DS algorithm, while having superior and more robust quality, similar to that of the Full Search algorithm.

A novel fast two step sub-pixel motion estimation algorithm in HEVC

Motion estimation (ME) is one of the most time consuming parts in video coding standard. As fast integer-pixel ME algorithm becoming more and more powerful, it is important to develop fast sub-pixel ME algorithm since the computational complexity of sub-pixel ME compared to integer-pixel ME has become relatively significant. In this paper, a novel fast sub-pixel ME algorithm is proposed. This algorithm first approximates the error surface of the sub-pixel position by a second order function and predicts the minimum point by minimizing the function at half-pixel accuracy. Then another second order approximation within a smaller area which is determined by the previous step is modeled to predict the best sub-pixel position. Experimental results show that the proposed method can reduce the sub-pixel search points significantly with negligible quality degradation.

Fast and efficient motion estimation using diamond zonal-based algorithms

Motion estimation has always been an important part of video encoding systems because it can reduce temporal redundancy effectively and thus has significant impact on the bit rate and the output visual quality of the encoded sequence. Unfortunately, when using the brute-force full search algorithm, motion estimation consumes a very large portion of the encoding time. Previously, several algorithms have been proposed which try to reduce complexity, usually, with a significant loss in visual quality. Based on the diamond zonal search framework we introduced recently, we propose in this paper a novel algorithm called advanced diamond zonal search (ADZS), which was submitted to and well received by the Moving Pictures Experts Group (MPEG) standard committee for possible inclusion as an encoder optimization tool. ADZS was criticized in MPEG for using fixed thresholds, which may not be suitable for all video sequences. To address this issue, we further propose a threshold-adaptive version called threshold-adaptive advanced diamond zonal search (TAADZS). Simulation results verify the superior performance of ADZS and TAADZS over other fast algorithms and the robustness of TAADZS over ADZS.

A robust interpolation-free approach for sub-pixel accuracy motion estimation

Motion estimation (ME) is one of the key elements in video coding standard which eliminates the temporal redundancy by using a motion vector (MV) to indicate the best match between the current frame and reference frame. A coarse to fine process is taken to find the best MV. First of all, integer-pixel ME finds a coarse MV and followed by the sub-pixel ME around the best integer-pixel point. The sub-pixel ME plays an important role in improving the coding efficiency. However, the computational complexity of searching one sub-pixel point is much higher than the integer-pixel point searching because of the interpolation and Hadamard transform operation. In this paper, an accurate optimal sub-pixel position prediction algorithm is presented. With the information of the 8 neighboring integer-pixel points, the optimal sub-pixel position is predicted directly without explicitly solving model parameters. Moreover, an outlier rejection scheme is applied to improve the robustness of the proposed algorithm. Experimental results show that the proposed algorithm outperforms the state of the art interpolation-freesub-pixel ME algorithms.

Fast sub-pixel motion estimation with simplified modeling in HEVC

Motion estimation (ME) is one of the key elements in video coding standard which eliminates the temporal redundancies between successive frames. In recent international video coding standards, sub-pixel ME is proposed for its excellent coding performance. Compared with integer-pixel ME, sub-pixel ME needs interpolation to get the value in sub-pixel position. Also, Hadamard transform will be applied in order to achieve better performance. Therefore, it is becoming more and more critical to develop fast sub-pixel ME algorithms. In this paper, a novel fast sub-pixel ME algorithm is proposed which makes full use of 8 neighboring integer-pixel points. This algorithm models the error surface in sub-pixel position by a second order function with five parameters two times to predict the best sub-pixel position. Experimental results show that the proposed method can reduce the complexity significantly with negligible quality degradation.