Computational Complexity Of Motion Estimation Research Articles

Algorithm and Architecture for Adaptive Motion Estimation in Video Processing

This paper introduces a block-based motion estimation algorithm based on projection with Adaptive Window Size Selection (AWSS) along with its architecture. Motion field of pixel is either horizontal or vertical, this paper assume horizontal and all the processing is done based on it. This projection method is combined with AWSS in which appropriate search window for each block is determined on the basis of motion vectors and prediction errors obtained for the previous block, which makes this novel method several times faster than exhaustive search with negligible performance degradation. Encoding QCIF-size video by the proposed method results in reduction of computational complexity of motion estimation by roughly 45% and overall encoding by 23%, while maintaining image/video quality. A hardware architecture for the adaptive motion estimation algorithm was also done in this paper, which has several features such as low latency less area and more speed which is applicable for 30 frames per sec with frame size of QCIF (176 × 144) which has a small chip area of (3.57 × 3.57 mm2) and operating frequency of 83 MHz 1.8 v, 195 mW power dissipation designed for video coding, with UMC 0.18 μm 1P6M cell library.

Architecture design of low-power motion estimation based on DHS-NPDS for H.264/AVC

A novel architecture of motion estimation (ME) based on improved normalized partial distortion search is proposed to meet three primary requirements for real-time video encoding, which are low-power, low- bandwidth and high area utilization efficiency. The ME engine supports both normalized partial distortion search and adaptive search window adjustment. The former can reduce the computational complexity of ME to save power and area; the latter can avoid unnecessary accessing the external memory to lower the data bandwidth. The proposed engine has been implemented with UMC 90nm CMOS technology. The implementation results show that, compared with traditional engines, the engine can achieve significant improvements of the hardware efficiency and the power efficiency respectively with a little throughput compromise.

Fast mode decision algorithm for extended macroblock motion estimation in key technology areas

Block sizes larger than the traditional 16×16 macroblock (MB) structure and extended macroblock (EMB) size motion estimation (ME) are introduced in joint model key technology areas software to improve the inter block coding efficiency. Similar to H.264, variable size motion estimation (VS-ME) is still adopted for each 16×16 MB including 16×16, 16×8, 8×16, 8×8, 8×4, 4×8, and 4×4. EMB size ME and VS-ME achieve the highest possible coding efficiency, but result in extremely large coding time which obstructs it from practical use. A fast mode decision algorithm for EMBs based on motion homogeneity is proposed to reduce the computational complexity of ME. The basic idea of the proposed method is to utilize the spatial property of motion field in prediction where EMB size ME and small size ME (including 8×8, 8×4, 4×8 and 4×4) are needed, and only in these regions EMB size ME and small size ME are enabled. The motion field is generated by the corresponding motion vectors in spatial window. Simulation results show that the proposed algorithm can save 55% average computational complexity, with negligible loss of coding efficiency.

基于DHS-NPDS 的低功耗运动估计硬件结构设计

A novel architecture of motion estimation (ME) based on improved normalized partial distortion search is proposed to meet three primary requirements for real-time video encoding, which are low-power, low- bandwidth and high area utilization efficiency. The ME engine supports both normalized partial distortion search and adaptive search window adjustment. The former can reduce the computational complexity of ME to save power and area; the latter can avoid unnecessary accessing the external memory to lower the data bandwidth. The proposed engine has been implemented with UMC 90nm CMOS technology. The implementation results show that, compared with traditional engines, the engine can achieve significant improvements of the hardware efficiency and the power efficiency respectively with a little throughput compromise.

Adaptive Return Prediction Block Matching Algorithms for Video Coding

As the development of network learning, video compression is important for both data transmission and storage, especially in a digit channel. In this paper, we present the return prediction search (RPS) algorithm for block motion estimation. The proposed algorithm exploits the temporal correlation and characteristic of returning origin to obtain one or two predictive motion vector and selects one motion vector, which presents better result, to be the initial search center. In addition, we utilize the center-biased block matching algorithms to refine the final motion vector. Moreover, we used adaptive threshold technique to reduce the computational complexity in motion estimation. Experimental results show that RPS algorithm combined with 4SS, BBGDS, and UCBDS effectively improves the performance in terms of mean-square error measure with less average searching points. On the other hand, accelerated RPS (ARPS) algorithm takes only 38% of the searching computations than 3SS algorithm, and the reconstruction image quality of the ARPS algorithm is superior to 3SS algorithm about 0.30dB in average overall test sequences. In addition, we create an asynchronous learning environment which provides students and instructors flexibility in learning and teaching activities. The purpose of this web site is to teach and display our researchable results. Therefore, we believe this web site is one of the keys to help the modern student achieve mastery of complex Motion Estimation.

Computation-aware fast motion estimation for H.264/AVC using image indexing

The key to designing a real-time video coding system is efficient motion estimation, which reduces temporal redundancies. The motion estimation of the H.264/AVC coding standard can use multiple references and multiple block sizes to improve rate-distortion performance. The computational complexity of H.264 is linearly dependent on the number of allowed reference frames and block sizes using a full exhaustive search. Many fast block-matching algorithms reduce the computational complexity of motion estimation by carefully designing search patterns with different shapes or sizes, which have a significant impact on the search speed and distortion performance. However, the search speed and the distortion performance often conflict with each other in these methods, and their high computational complexity incurs a large amount of memory access. This paper presents a novel block-matching scheme with image indexing, which sets a proper priority list of search points, to encode a H.264 video sequence. This study also proposes a computation-aware motion estimation method for the H.264/AVC. Experimental results show that the proposed method achieves good performance and offers a new way to design a cost-effective real-time video coding system.

Adaptive search range adjustment scheme for fast motion estimation in AVC/H.264

AVC/H.264 supports the use of multiple reference frames (e.g., 5 frames in AVC/H.264) for motion estimation (ME), which demands a huge computational complexity in ME. We propose an adaptive search range adjustment scheme to reduce the computational complexity of ME by reducing the search range of each reference frame-from the (t-1)'th frame to the (t-5)'th frame-for each macroblock. Based on the statistical analysis that the 16×16 mode type is dominantly selected rather than the other block partition mode types, the proposed method reduces the search range of the remaining ME process in the given reference frame according to the motion vector (MV) position of the 16×16 block ME. In the case of the (t-1)'th frame, the MV position of the 8×8 block ME-in addition to that of 16×16 block ME-is also used for the search range reduction to sub-block partition mode types of the 8×8 block. The experimental results show that the proposed method reduces about 50% and 65% of the total encoding time over CIF/SIF and full HD test sequences, respectively, without any noticeable visual degradation, compared to the full search method of the AVC/H.264 encoder.

Weighted constrained one-bit transform based fast block motion estimation

Block based motion estimation (ME) techniques based on low bit-depth representation have been proposed in the literature to reduce the computational complexity of ME. One-bit transform based ME methods are pioneers in this field. These methods derive one-bit images using an adaptive thresholding scheme, and perform block based ME on one-bit images using simplified matching criteria. Recently, constrained one-bit transform (C-1BT) based ME has been proposed to increase ME performance of 1BT based ME, restraining pixels with values close to the adaptive threshold throughout the matching. In this work, a weighted constraint strategy is proposed to increase the matching performance of C-1BT based ME. Instead of the one-bit constraint mask used in the literature, a two-bit constraint is computed according to the difference between a pixel and its 1BT threshold value, novel to this paper. Experimental results show that the proposed method improves the ME performance of C-1BT, and outperforms other low bit-depth based ME methods at macro-block level.

Low-Complexity Motion Estimation for H.264/AVC Through Perceptual Video Coding

This paper presents a low-complexity algorithm for an H.264/AVC encoder. The proposed motion estimation scheme determines the best coding mode for a given macroblock (MB) by finding motion-blurred MBs; identifying, before motion estimation, an early selection of MBs; and hence saving processing time for these MBs. It has been observed that human vision is more sensitive to the movement of well-structured objects than to the movement of randomly structured objects. This study analyzed permissible perceptual distortions and assigned a larger inter-mode value to the regions that are perceptually less sensitive to human vision. Simulation results illustrate that the algorithm can reduce the computational complexity of motion estimation by up to 47.16% while maintaining high compression efficiency.

FAST BLOCK MOTION ESTIMATION WITH EDGE ALIGNMENT ON H.264 VIDEO CODING

This paper presents a novel block matching scheme with edge alignment strategy on H.264 video coding. which uses multiple references and multiple block Sizes for motion estimation in order to improve the rate-distortion performance. In H.264. the computational complexity is linearly dependent on the number of allowed reference frames and block sizes using the full exhaustive search. Many fast block-matching algorithms reduce the computational complexity of motion estimation by carefully designing the search patterns with different shapes or sites which have significant impact on the search speed and distortion performance. However, the search speed and the distortion performance conflict often with each other for these methods. In this paper. given a block in the current frame. we first apply a fast approximate method based on edge alignment to obtain a good initial motion vector as well as a tight initial hound of distortion measure. Then, considering the edge orientation of the block, a modified hexagon search is used to fine tune the motion vector in low computation complexity. The proposed algorithm also pays attentions to the characteristics of multiple reference frames and multiple block sizes in H.264. Computer simulation results show that the proposed method gives good performance and pans a new way to design a cost-effective real-time video coding system.

Macroblock-level adaptive search range algorithm for motion estimation in multiview video coding

Multiview video coding (MVC) is an ongoing standard. In the working draft, motion estimation and disparity estimation are both employed in the encoding procedure. It achieves the highest possible coding efficiency, but results in extremely large encoding time, which obstructs it from practical applications. We propose a macroblock (MB) level adaptive search range algorithm utilizing inter-view correlation for motion estimation in MVC to reduce the complexity of the coder. For multi-view sequences, the motion vectors of the corresponding MBs in previously coded view are first extracted to analyze motion homogeneity. On the basis of motion homogeneity, MBs are classified into three types (MB in the region with homogeneous motion, with medium homogeneous motion, or with complex motion), and search range is adaptively determined for each type MB. Experimental results show that our algorithm can save 75% average computational complexity of motion estimation, with negligible loss of coding efficiency.

Two-bit transform based block motion estimation using second derivatives

Binary motion estimation algorithms reduce the computational complexity of motion estimation, but, sometimes generate an inaccurate motion vector. This paper proposes a novel two-bit representation, called twobit transform-second derivatives (2BT-SD) which improves the efficiency of image binarization and the accuracy of motion estimation by making use of the positive and negative second derivatives independently in the derivation of the second bit plane. The second derivatives are also used to detect flat or background regions, avoiding expensive motion vector search operations for macroblocks in these areas, and deriving the motion vectors by prediction from neighboring blocks. In applying the proposed 2BT-SD in the H.264/AVC standard, a further reduction of motion estimation complexity with a minor accuracy reduction is achieved by using 2BT-SD representation for secondary motion estimation while using the full resolution representation for the primary motion estimation. A hardware cost analysis shows that about 209 K gates of hardware logics and 2.7 K bytes of memory are reduced by 2BT-SD for motion estimation of 1280times720 size videos when compared with the full resolution motion estimation. Experiments show that the proposed 2BT-SD achieves better motion estimation accuracy than other binary motion estimations and provides faster processing time in flat or background regions with an acceptable bit-rate increase.

B 슬라이스의 압축 효율 향상을 위한 개선된 양방향 대칭 예측 부호화 방법

H.264/AVC의 B 슬라이스의 부호화 효율 향상과 두 개의 움직임벡터를 탐색하는데 소요되는 계산량 감소를 위하여 양방향 대칭(Bi-directional Symmetric) 기법이 개발된 바 있다. 이 기법은, 전방향과 역방향 참조영상 각각에 대하여 움직임 벡터를 구하고 이 두 개를 각각 다 전송하는 종래의 양방향 예측기법과는 달리, 전방향 참조영상에 대해 움직임 벡터를 찾는 동시에 역방향 참조영상에 대한 역방향 움직임 벡터를 전방향 참조영상, 역방향 참조영상, 그리고 현재 영상간의 상대적 거리를 고려한 대칭(Symmetric) 구조로 동시에 계산하여 추정하는 방법이다. 이 기법에 따르면, 전방향 움직임 벡터가 정해지면, 역방향 움직임벡터는 이와 대칭적으로 계산하여 얻어지므로 움직임벡터 추정 복잡도를 반으로 줄이고, 전방향 움직임벡터만을 전송하도록 하여 부호화할 움직임벡터의 양도 줄일 수 있다. 그러나 이 방법은 항상 전방향 움직임 벡터를 기준으로 역방향 움직임 벡터를 계산하여 얻다 보니, 장면전환등의 경우 오히려 역방향 움직임벡터를 기준으로 전방향 움직임벡터를 추산하는 것이 더욱 효율적인 경우도 있다. 본 논문에서는 전방향 참조영상에 대한 움직임 벡터를 중심으로 역방향 움직임 예측벡터를 추정하는 방법을 일반화시켜, 역방향 움직임 벡터를 중심으로 전방향 움직임 벡터를 추산하여 사용하는 방법을 제안하고 아울러 기존 방법과 제안 방법을 율왜곡 관점에서 최적으로 선택하여 사용하는 방법을 제안한다. A bi-directional symmetric prediction technique has been developed to improve coding efficiency of B-slice and to reduce the computational complexity required to estimate two motion vectors. On the contrary to the conventional bi-directional mode which encodes both forward and backward motion vectors, it only encodes a single forward motion vector, and the missing backward motion vector is derived in a symmetric way from the forward motion vector using temporal distance between forward/backward reference frames to and from the current B picture. Since the backward motion vector is derived from the forward motion vector, it can halve the computational complexity for motion estimation, and also reduces motion vector data to encode. This technique always derives the backward motion vector from the forward motion vector, however, there are cases when the forward motion vector is better to be derived from the backward motion vector especially in scene changes. In this paper, we generalize the idea of the symmetric coding with forward motion vector coding, and propose a new symmetric coding with backward motion vector coding and adaptive selection between the conventional symmetric mode and the proposed symmetric mode based on rate-distortion optimization.

Content-Aware Prediction Algorithm With Inter-View Mode Decision for Multiview Video Coding

3-D video will become one of the most significant video technologies in the next-generation television. Due to the ultra high data bandwidth requirement for 3-D video, effective compression technology becomes an essential part in the infrastructure. Thus multiview video coding (MVC) plays a critical role. However, MVC systems require much more memory bandwidth and computational complexity relative to mono-view video coding systems. Therefore, an efficient prediction scheme is necessary for encoding. In this paper, a new fast prediction algorithm, content-aware prediction algorithm (CAPA) with inter-view mode decision, is proposed. By utilizing disparity estimation (DE) to find corresponding blocks between different views, the coding information, such as rate-distortion cost, coding modes, and motion vectors, can be effectively shared and reused from the coded view channel. Therefore, the computation for motion estimation (ME) in most view channels can be greatly reduced. Experimental results show that compared with the full search block matching algorithm (FSBMA) applied to both ME and DE, the proposed algorithm saves 98.4-99.1% computational complexity of ME in most view channels with negligible quality loss of only 0.03-0.06 dB in PSNR.

Fast Inter Mode Decision Using Spatial Property of Motion Field

Variable size motion estimation with multiple reference frames has been adopted by the new video coding standard H.264. It can achieve significant coding efficiency compared to coding a macroblock (MB) in regular size with single reference frame. On the other hand, it causes high computational complexity of motion estimation at the encoder. Rate distortion optimized (RDO) decision is one powerful method to choose the best coding mode among all combinations of block sizes and reference frames, but it requires extremely high computation. In this paper, a fast inter mode decision is proposed to decide best prediction mode utilizing the spatial continuity of motion field, which is generated by motion vectors from 4times4 motion estimation. Motion continuity of each MB is decided based on the motion edge map detected by the Sobel operator. Based on the motion continuity of a MB, only a small number of block sizes are selected in motion estimation and RDO computation process. Simulation results show that our algorithm can save more than 50% computational complexity, with negligible loss of coding efficiency.

Content-Aware Fast Motion Estimation for H.264/AVC

The key to high performance in video coding lies on efficiently reducing the temporal redundancies. For this purpose, H.264/AVC coding standard has adopted variable block size motion estimation on multiple reference frames to improve the coding gain. However, the computational complexity of motion estimation is also increased in proportion to the product of the reference frame number and the intermode number. The mathematical analysis in this paper reveals that the prediction errors mainly depend on the image edge gradient amplitude and quantization parameter. Consequently, this paper proposes the image content based early termination algorithm, which outperforms the original method adopted by JVT reference software, especially at high and moderate bit rates. In light of rate-distortion theory, this paper also relates the homogeneity of image to the quantization parameter. For the homogenous block, its search computation for futile reference frames and intermodes can be efficiently discarded. Therefore, the computation saving performance increases with the value of quantization parameter. These content based fast algorithms were integrated with Unsymmetrical-cross Multihexagon-grid Search (UMHexagonS) algorithm to demonstrate their performance. Compared to the original UMHexagonS fast matching algorithm, 26.14–54.97% search time can be saved with an average of 0.0369 dB coding quality degradation.

Projection Based Adaptive Window Size Selection for Efficient Motion Estimation in H.264/AVC

This paper introduces a block based motion estimation algorithm based on projection with adaptive window size selection. The blocks cannot match well if their corresponding 1D projection does not match well, with this as foundation 2D block matching problem is translated to a simpler 1D matching, which eliminates majority of potential pixel participation. This projection method is combined with adaptive window size selection in which, appropriate search window for each block is determined on the basis of motion vectors and prediction errors obtained for the previous block, which makes this novel method several times faster than exhaustive search with negligible performance degradation. Encoding QCIF size video by the proposed method results in reduction of computational complexity of motion estimation by roughly 45% and over all encoding by 23%, while maintaining image/video quality.

Fast Variable Block Size Motion Estimation for H.264 Using Likelihood and Correlation of Motion Field

Variable block size motion compensation has been adopted by the emerging video coding standard H.264. It can represent the motion characteristic in a macroblock more accurately and, therefore, reduces the prediction error to achieve high compression gains. On the other hand, it causes high computational complexity in motion estimation at the encoder. The motion estimation exhaustively performed over all modes to find the best mode for inter coding is slow and computationally involved. In order to reduce the complexity, we proposed a fast inter mode decision algorithm for H.264 encoder. The proposed method efficiently determines a suitable block mode according to the motion field distribution and correlation within a macroblock. The experimental results show that the proposed method reduces a considerable amount of complexity at encoder, while the rate-distortion performance of the proposed method is comparable to that of full mode search

Fast digital image stabilization using one bit transform based sub-image motion estimation

This paper presents a fast image sequence stabilization system that uses one bit transform (IBT) matching based global motion estimation and Kalman filtering based global motion correction. In order to facilitate a fast motion estimation process, image frames are initially converted into a single bit-plane representation using the IBT, and then motion vectors are evaluated matching the IBTs of two consecutive frames using Boolean operations. Because a binary representation is established, the computational complexity of motion estimation is significantly reduced providing a proportionate reduction in power consumption of custom hardware. The global motion vector is computed using local motion vectors of sub-image blocks to further increase the motion estimation speed. For the motion correction part, global motion vectors are accumulated to yield absolute frame displacements and Kalman filtering is employed to achieve stabilization.

Motion Estimation Using Spatio-Temporal Contextual Information

Motion estimation is an important and computationally intensive task in video coding applications. Block-matching-based fast algorithms reduce the computational complexity of motion estimation at the expense of accuracy. An analysis of computation and performance trade-offs in motion estimation algorithms helps in choosing a suitable algorithm for video/visual communication applications. Fast motion estimation algorithms often assume a monotonic error surface in order to speed up the computations involved in motion estimation. The argument against this assumption is that the search might be trapped in local minima resulting in inaccurate motion estimates. The paper investigates state-of-the-art techniques for block-based motion estimation and presents an approach to improving the performance of block-based motion estimation algorithms. Specifically, the paper suggests a simple scheme that includes spatio-temporal neighborhood information for obtaining better estimates of the motion vectors. The paper also investigates the effects of the monotonic error surface assumption and suggests a remedy to reduce its impact on the motion field estimates. The presented experiments demonstrate the efficiency of the proposed approach.