Full Search Motion Estimation Algorithm Research Articles

Protection of Ultrasound Image Sequence: Employing Motion Vector Reversible Watermarking

In healthcare information systems, medical data is very important for diagnosis. Most of the health institutions store their patients’ data on third-party servers. Therefore, its security is very important, since the advent of advanced multimedia and communication technology, whereby digital contents are manipulated, copied, and duplicated without leaving any trace. In this paper, a reversible watermarking technique is applied to the patients’ data (ultrasound image sequence). Since the traditional watermarking schemes can experience some permanent distortions that are not acceptable in the medical application. Thus, a reversible watermarking technique has been used, which can not only secure the ultrasound image sequence but also restore the original sequence back. For watermark embedding, the magnitude and phase angles of motion vectors of the image sequence are used that are obtained by using Full-Search block-based motion estimation algorithm. Before applying the motion estimation algorithm and watermark embedding, the histogram pre-processing is performed to avoid underflow/overflow. Unlike other state-of-the-art watermarking schemes that are reported in the last decades, the experimental results show that the proposed algorithm is simple, provides a much larger embedding capacity and better quality of the watermarked image sequence.

An efficient multi-layer reference frame motion estimation for video coding

Most of the fast search motion estimation algorithms reduce the computational complexity of motion estimation (ME) greatly by checking only a few search points inside the search area. In this paper, we propose a new algorithm--multi-layer motion estimation (MME) which reduces the computational complexity of each distortion measure instead of reducing the number of search points. The conventional fast search motion estimation algorithms perform ME on the reference frame with full distortion measure; on the contrary, the MME performs ME on the layers with partial distortion measures to enhance the computational speed of ME. A layer is an image which is derived from the reference frame; each macro-pixel value in the layer represents the sum of the values of the corresponding pixels in the reference frame. A hierarchical quad-tree structure is employed in this paper to construct multiple layers from the reference frame. Experimental results on different video sequences show evidence that many motion vectors have been found similar both in the reference frame and the layers. The effectiveness of the proposed MME algorithm is compared with that of some state-of-the-art fast block matching algorithms with respect to speed and motion prediction quality. Experimental results on a wide variety of video sequences show that the proposed algorithm outperforms the other popular conventional fast search motion estimation algorithms computationally while maintaining the motion prediction quality very close to the full-search algorithm. Moreover, the proposed algorithm can achieve a maximum of 97.99 % speed-improvement rate against the fast full-search motion estimation algorithms which are based on hierarchical block matching process. The proposed MME performs the motion estimation on the layers by using three types of search patterns. The derivation of these search patterns exploits the characteristic of the center-biased motion vector distribution and that of less intensive block distortion measurement of the layers.

The efficient optimal and suboptimal motion estimation algorithms

The new fast full-search motion estimation algorithm for optimal motion estimation is proposed in this paper. This algorithm presents fast computing method that calculates the tighter boundaries faster by exploiting the computational redundancy. The proposed algorithm, first, determines the possible motion vectors (PMVs) that are not rejected by the first two tighter boundaries to facilitate the prediction of the best initial motion vector (IMV) for the follow-up search. Thereafter, an optimal motion vector (OMV) will be traced out in the PMV set. The IMV greatly helps in the early rejection of impossible candidate blocks while tracing the OMV. Experimental results show that the proposed algorithm outperforms the other previous optimal motion estimation algorithms in reducing the number of computations on several video sequences. The proposed algorithm achieves about 156–456 speed-up gain over full search on several video sequences. But, the state-of-the-art algorithms such as adaptive MSEA and Winner Update algorithm with Integral image algorithms can achieve only about 72–382 speed-up gain over full search on the same video sequences. Finally, the proposed new fast full-search motion estimation algorithm is modified to suboptimal motion estimation algorithm, resulting only in a trivial average peak signal-to-noise ratio drop of about 0.2 dB, but it achieves a very fast computational speed.

Parallelization of Full Search Motion Estimation Algorithm for Parallel and Distributed Platforms

This work presents an efficient method to map the Full Search algorithm for Motion Estimation (ME) onto General Purpose Graphic Processing Unit (GPGPU) architectures using Compute Unified Device Ar...

RD Optimized Bandwidth Efficient Motion Estimation and Its Hardware Design With On-Demand Data Access

Data bandwidth dominates the performance and power consumption in the video encoder design. In which a low bandwidth and bandwidth aware motion estimation design enables smooth and better video quality as well as lower power consumption on data accesses. This paper proposes a bandwidth efficient motion estimation and its hardware implementation to deal with the bandwidth issues. First, an on-demand data access mechanism is proposed to acquire the reference data according to the video content for motion estimation process and thus can avoid unnecessary reference data loading. Furthermore, the available bandwidth constraint is properly modeled into our proposed rate distortion optimization framework to efficiently use the data bandwidth. Simulation results show that our proposed algorithm not only allocates proper data bandwidth for motion estimation according to video content but also saves 79.15% data bandwidth demand with 0.03 dB PSNR drop and 2.50% bitrate increase in maximum for 4 CIF resolution sequences, when compared to the fully data reuse full search motion estimation which reuses the overlapped reference data to avoid unnecessary data reloading. In addition, under the available data bandwidth constraint, our proposed algorithm can achieve 2.43%, 0.08%, and 0.20% BD-bitrate saving with 0.17 dB, 0.01 dB, and 0.01 dB BD-PSNR increase on average for high, median, and low motion sequences when compared to the full search motion estimation algorithm. The resulted design only needs 75.27 K gate counts when running at 23 MHz operating frequency for 4 CIF at 30 frames/s with 90 nm CMOS process due to its search range independent buffer design.

Efficient two step edge based partial distortion search for fast block motion estimation

In video coding, block based full search motion estimation algorithm has been widely used, but it suffers from high computational requirements. In order to reduce the computations, this paper proposes a novel edge based partial distortion search (EPDS) algorithm which reduces the computation of each distortion measure by using partial distortion search. In this algorithm, the entire macroblock (MB) is divided into different sub-blocks and the calculation order of partial distortion is determined based on the edge strength of sub-blocks. This algorithm adaptively changes the early termination threshold for every accumulated partial sum of absolute difference. In the proposed method, only selected numbers of search points are considered for candidate motion vectors. An efficient early termination method, which is based on the dynamic threshold, is also proposed to decide whether a search point has met the rate-distortion (RD) cost criterion so that the best search point can be determined early. Simulation results show that the proposed method offers a remarkable improvement in computational speed when compared to full search (FS) and normalized partial distortion search (NPDS) algorithms. The proposed method is 115 times faster than FS, 10 times faster than NPDS and 2 times faster than the dual halfway stop NPDS (DHS-NPDS) on an average. PSNR degradation of the proposed algorithm is negligible and in the region of 0.01 dB. The proposed method can be easily applied to many mobile video application areas such as digital cameras and DMB (Digital Multimedia Broadcasting) phones.

New fast full search algorithms using DCT coefficients

This paper presents new fast full search motion estimation (ME) algorithms using discrete cosine transform (DCT) coefficients as a gradient magnitude. The proposed algorithms use intra DCT coefficients to arrange the matching scan order. The proposed algorithm 1 uses some of DCT coefficients based on the relationship between gradient magnitude and DCT coefficients, and the proposed algorithm 2 uses all of DCT alternating current (AC) coefficients in order to predict the fluctuation of a block. The proposed algorithms significantly reduce the computational complexity of the conventional algorithm while maintaining the visual quality of video.

Edge Block Detection and Motion Vector Information Based Fast VBSME Algorithm

Compared with previous standards, H.264/AVC adopts variable block size motion estimation (VBSME) and multiple reference frames (MRF) to improve the video quality. Full search motion estimation algorithm (FS), which calculates every search candidate in the search window for 7 block type with multiple reference frames, consumes massive computation power. Mathematical analysis reveals that the aliasing problem of subsampling algorithm comes from high frequency signal components. Moreover, high frequency signal components are also the main issues that make MRF algorithm essential. As we know, a picture being rich of texture must contain lots of high frequency signals. So based on these mathematical investigations, two fast VBSME algorithms are proposed in this paper, namely edge block detection based subsampling method and motion vector based MRF early termination algorithm. Experiments show that strong correlation exists among the motion vectors of those blocks belonging to the same macroblock. Through exploiting this feature, a dynamically adjustment of the search ranges of integer motion estimation is proposed in this paper. Combing our proposed algorithms with UMHS almost saves 96–98% Integer Motion Estimation (IME) time compared to the exhaustive search algorithm. The induced coding quality loss is less than 0.8% bitrate increase or 0.04 dB PSNR decline on average.

Variable step search fast motion estimation for H.264/AVC video coder

In this paper, we propose a variable step search fast motion estimation algorithm using local statistics of neighboring motion vectors. Using the degree of correlation between neighboring motion vectors, motion search range of each macroblock is adaptively adjusted to reduce unnecessary search points. Based on the determined search range, motion vector is obtained by variable step search step. Experimental results show that comparing to fast full spiral search, fixed step, and fast variable block size motion estimation algorithms, the motion search points and computing time of proposed algorithm are dramatically reduced with acceptable loss in coding performance.

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.

A hardware implementation for full-search motion estimation of AVS with search center prediction

This paper presents a full search motion estimation algorithm with search center prediction for AVS and the VLSI architecture to realize the algorithm. The proposed algorithm achieves comparable performance in coding efficiency with the anchor algorithm, whereas has low storage requirement, low required bandwidth and low complexity for the hardware implementation. The proposed architecture adopts 1-D PE arrays architecture and can perform variable block size motion estimation with 70 k logic gates and 24 kbits on-chip memory. The architecture achieves best tradeoff in terms of speed and hardware cost. The design can satisfy real-time encoding for AVS high definition application of 1280times720 picture size at 60 fps

A rate-constrained fast full-search algorithm based on block sum pyramid

This paper presents a fast full-search algorithm (FSA) for rate-constrained motion estimation. The proposed algorithm, which is based on the block sum pyramid frame structure, successively eliminates unnecessary search positions according to rate-constrained criterion. This algorithm provides the identical estimation performance to a conventional FSA having rate constraint, while achieving considerable reduction in computation.

Fast Full-Search Motion Estimation Based on Multilevel Successive Elimination Algorithm

An improved fast full-search algorithm for motion estimation is proposed. The computational process of the sum of absolute difference and the multilevel successive elimination algorithm (MSEA) are theoretically analysed. Based on these analyzes, a new detection criterion and an estimation of the starting level are proposed in order to reduce the computations required for judging invalid candidate blocks. The simulation results show that the proposed algorithm achieves a computational timesaving of about 40% compared with the MSEA.

Fast full search motion estimation algorithm using early detection of impossible candidate vectors

To reduce the amount of computations for a full search (FS) algorithm for fast motion estimation, we propose a new and fast FS motion estimation algorithm. The computational reduction of our FS motion estimation algorithm comes from fast elimination of impossible motion vectors. We obtain faster elimination of inappropriate motion vectors using efficient matching units from localization of a complex area in image data. In this paper, we show three properties in block matching of motion estimation. We suggest two fast matching scan algorithms: one from adaptive matching scan and the other from fixed dithering order. Experimentally, we remove the unnecessary computations by about 30% with our proposed algorithm compared with the conventional fast FS algorithms.

A complexity-bounded motion estimation algorithm

The full search motion estimation algorithm for video coding is a procedure of high computational cost. For this reason, in real-time low-power applications, low-cost motion estimation algorithms are viable solutions. A novel reduced complexity motion estimation algorithm is presented. It conjugates the reduction of computational load with good encoding efficiency. It exploits the past history of the motion field to predict the current motion field. A successive refinement phase gives the final motion field. This approach leads to a sensible reduction in the number of motion vector that have to be tested. The complexity is lower than any other algorithm algorithms known to the authors, in the literature, it is constant as there is no recursivity in the algorithm and independent of any search window area size. Experimental evaluations have shown the robustness of the algorithm when applied on a wide set of video sequences--a good performance compared to other reduced complexity algorithms and negligible loss of efficiency versus the full search algorithm.

A fast full search motion estimation algorithm using sequential rejection of candidates from hierarchical decision structure

We propose a new as well as fast full search (FS) motion estimation algorithm for video coding. The computational reduction comes from sequential rejection of impossible candidates with derived formula and subblock norms. Our algorithm reduces more the computations than the FS motion estimation algorithms previously developed.

Fast full search motion estimation algorithm using various matching scans in video coding

To reduce the amount of computation in a full search (FS) algorithm for fast motion estimation, we propose a novel and fast FS motion estimation algorithm. The computational reduction without any degradation in the predicted image comes from fast elimination of impossible motion vectors. We obtain faster elimination of inappropriate motion vectors using efficient matching units from localization of the complex area in image data. We show three properties in block matching of motion estimation. We suggest two fast matching scan algorithms, one from adaptive matching scan and the other from fixed dithering order. Experimentally, we remove the unnecessary computations by about 30% with our proposed algorithm compared to conventional fast matching scan algorithms.

A fast full-search motion-estimation algorithm using representative pixels and adaptive matching scan

A full-search based block-matching algorithm for motion estimation has a major problem of significant computational load. To solve this problem, extensive research in fast-motion estimation algorithms have been carried out. However, most of them have some degradation in the predicted image from the reduced computation. To decrease the amount of significant computation of the full-search algorithm, we propose a fast block-matching algorithm based on an adaptive matching scan and representative pixels without any degradation of the predicted image. By using Taylor series expansion, we obtain the representative pixels and show that the block-matching errors from the reference block and candidate blocks are proportional to the block complexity. With the derived result, we propose a fast full-search algorithm with adaptive scan direction in block matching. Experimentally, our proposed algorithm is very efficient in terms of computational speedup, and is the fastest among all the conventional full-search algorithms. Therefore, our algorithm is useful in VLSI implementation of video encoders for real-time encoding.

Cost Effective VLSI Architectures for Full-SearchBlock-Matching Motion Estimation Algorithm

In this paper, we present efficient VLSI architectures for full-search block-matching motion estimation (BMME) algorithm. Given a search range, we partition it into sub-search arrays called tiles. By fully exploiting data dependency within a tile, efficient VLSI architectures can be obtained. Using the proposed VLSI architectures, all the block-matchings in a tile can be processed in parallel. All the tiles within a search range can be processed serially or concurrently depending on various requirements. With the consideration of processing speed, hardware cost, and I/O bandwidth, the optimal tile size for a specific video application is analyzed. By partitioning a search range into tiles with appropriate size, flexible VLSI designs with different throughput can be obtained. In this way, cost effective VLSI designs for a wide range of video applications, from H.261 to HDTV, can be achieved.

Mapping real-time motion estimation type algorithms to memory efficient, programmable multi-processor architectures

In this paper, an architectural template is presented, which is able to execute the full search motion estimation algorithm or other similar video or image processing algorithms in real time. The architecture is based on a set of programmable video signal processors (VSP's). It is also possible to integrate the processor cores and their local memories on a (set of) chip(s). Due to the programmability, the system is very flexible and can be used for emulation of other similar block-oriented local-neighborhood algorithms. The architecture can be easily divided into several partitions, without data-exchange between partitions. Special attention is paid to memory size and transfer optimization, which are dominant factors for both area and power cost. The trade-offs and techniques used to arrive at these solutions are explained in detail. It is shown that careful optimizations can lead to large savings in memory size (up to 66%) and bandwidth requirements (up to a factor of 4) compared to a straightforward solution.