Lai-Man Po

A novel four-step search algorithm for fast block motion estimation

Based on the real world image sequences characteristic of center-biased motion vector distribution, a new four-step search (4SS) algorithm with center-biased checking point pattern for fast block motion estimation is proposed in this paper. A halfway-stop technique is employed in the new algorithm with searching steps of 2 to 4 and the total number of checking points is varied from 17 to 27. Simulation results show that the proposed 4SS performs better than the well-known three-step search and has similar performance to the new three-step search (N3SS) in terms of motion compensation errors. In addition, the 4SS also reduces the worst-case computational requirement from 33 to 27 search points and the average computational requirement from 21 to 19 search points, as compared with N3SS.

A novel cross-diamond search algorithm for fast block motion estimation

In block motion estimation, search patterns with different shapes or sizes and the center-biased characteristics of motion-vector distribution have a large impact on the searching speed and quality of performance. We propose a novel algorithm using a cross-search pattern as the initial step and large/small diamond search (DS) patterns as the subsequent steps for fast block motion estimation. The initial cross-search pattern is designed to fit the cross-center-biased motion vector distribution characteristics of the real-world sequences by evaluating the nine relatively higher probable candidates located horizontally and vertically at the center of the search grid. The proposed cross-diamond search (CDS) algorithm employs the halfway-stop technique and finds small motion vectors with fewer search points than the DS algorithm while maintaining similar or even better search quality. The improvement of CDS over DS can be up to a 40% gain on speedup. Experimental results show that the CDS is much more robust, and provides faster searching speed and smaller distortions than other popular fast block-matching algorithms.

Edge-Based Structural Similarity for Image Quality Assessment

Objective quality assessment has been widely used in image processing for decades and many researchers have been studying the objective quality assessment method based on human visual system (HVS). Recently the structural similarity (SSIM) is proposed, under the assumption that the HVS is highly adapted for extracting structural information from a scene, and simulation results have proved that it is better than PSNR (or MSE). By deeply studying the SSIM, we find it fails in measuring the badly blurred images. Based on this, we develop an improved method which is called edge-based structural similarity (ESSIM). Experiment results show that ESSIM is more consistent with HVS than SSIM and PSNR especially for the blurred images

Normalized partial distortion search algorithm for block motion estimation

Many fast block-matching algorithms reduce computations by limiting the number of checking points. They can achieve high computation reduction, but often result in relatively higher matching error compared with the full-search algorithm. A novel fast block-matching algorithm named normalized partial distortion search is proposed. The proposed algorithm reduces computations by using a halfway-stop technique in the calculation of the block distortion measure. In order to increase the probability of early rejection of non-possible candidate motion vectors, the proposed algorithm normalized the accumulated partial distortion and the current minimum distortion before comparison. Experimental results show that the proposed algorithm can maintain its mean square error performance very close to the full-search algorithm while achieving an average computation reduction of 12-13 times, with respect to the full-search algorithm.

Novel cross-diamond-hexagonal search algorithms for fast block motion estimation

We propose two cross-diamond-hexagonal search (CDHS) algorithms, which differ from each other by their sizes of hexagonal search patterns. These algorithms basically employ two cross-shaped search patterns consecutively in the very beginning steps and switch using diamond-shaped patterns. To further reduce the checking points, two pairs of hexagonal search patterns are proposed in conjunction with candidates found located at diamond corners. Experimental results show that the proposed CDHSs perform faster than the diamond search (DS) by about 144% and the cross-diamond search (CDS) by about 73%, whereas similar prediction quality is still maintained.

Enhanced hexagonal search for fast block motion estimation

Fast block motion estimation normally consists of low-resolution coarse search and the following fine-resolution inner search. Most motion estimation algorithms developed attempt to speed up the coarse search without considering accelerating the focused inner search. On top of the hexagonal search method recently developed, an enhanced hexagonal search algorithm is proposed to further improve the performance in terms of reducing number of search points and distortion, where a novel fast inner search is employed by exploiting the distortion information of the evaluated points. Our experimental results substantially justify the merits of the proposed algorithm.

Adaptive motion tracking block matching algorithms for video coding

In most block-based video coding systems, the fast block matching algorithms (BMAs) use the origin as the initial search center, which may not track the motion very well. To improve the accuracy of the fast BMAs, a new adaptive motion tracking search algorithm is proposed. Based on the spatial correlation of motion blocks, a predicted starting search point, which reflects the motion trend of the current block, is adaptively chosen. This predicted search center is found closer to the global minimum, and thus the center-biased BMAs can be used to find the motion vector more efficiently. Experimental results show that the proposed algorithm enhances the accuracy of the fast center-biased BMAs, such as the new three-step search, the four-step search, and the block-based gradient descent search, as well as reduces their computational requirement.

Adjustable partial distortion search algorithm for fast block motion estimation

The quality control for video coding usually absents from many traditional fast block motion estimators. A novel block-matching algorithm for fast motion estimation named the adjustable partial distortion search algorithm (APDS) is proposed. It is a new normalized partial distortion comparison method capable of adjusting the prediction accuracy against searching speed by a quality factor k. With adjustability, APDS could act as the normalized partial distortion search algorithm (NPDS) when k is equal to 0, and the conventional partial distortion search algorithm (PDS) when k is equal to 1. In addition, it uses a halfway-stop technique with progressive partial distortions (PPD) to increase early rejection rate of impossible candidate motion vectors at very early stages. Simulations with PPD reduce computations up to 38 times with less than 0.50-dB degradation in PSNR performance, as compared to the full-search algorithm (FS). Experimental results show that APDS could provide peak signal-to-noise ratio performance very close to that of FS with speedup ratios of 7 to 16 times, and close to that of NPDS from 22 to 32 times, respectively, as compared to FS.

A fast H.264 intra prediction algorithm using macroblock properties

In the newest video coding standard of H.264, intra frame prediction is conducted in the spatial domain. There are two types of intra prediction for luma - Intra/spl I.bar/16/spl times/16 does prediction for the whole 16/spl times/16 luma macroblock and Intra/spl I.bar/4/spl times/4 does prediction for 4/spl times/4 block. Four and nine modes are supported by Intra/spl I.bar/16/spl times/16 and Intra/spl I.bar/4/spl times/4, respectively. The full search algorithm is used in the JVT reference software to choose the best modes, however it is very computationally expensive. In this paper, a new fast intra prediction algorithm using macroblock properties (FIPAMP) is proposed. Experimental results show that the proposed fast algorithm can achieve 10% to 40% computation reduction while maintaining similar PSNR and bit rate performance of H.264 codes.

Fast Bit Rate Estimation for Mode Decision of H.264/AVC

To achieve the highest coding efficiency, H.264/AVC uses rate-distortion optimization technique. This means that the encoder has to code the video by exhaustively trying all the mode combinations including the different intra- and inter-prediction modes. Therefore, the complexity and computation load of video coding in H.264/AVC increase drastically compared to any previous standards. To reduce the complexity of rate-distortion cost computation, we propose a fast bit rate estimation technique to avoid the entropy coding method during intra- and inter-mode decision of H.264/AVC. The estimation method is based on the properties of context-based variable length coding (CAVLC). The proposed rate model predicts the rate of a 4 times 4 quantized residual block using five different tokens of CAVLC. Experimental results demonstrate that the proposed estimation method reduces about 47% of total encoding time on using intra-modes only and saves about 34% of total encoding time on using both inter- and intra-modes with ignorable degradation of coding performance when the fast motion search algorithm is used. When full search motion estimation algorithm is used, the proposed algorithm reduces about 17% of total encoding time.