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International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS)

作者： Hussain, Abir Jaafar Knight, Liam Al-Jumeily, Dhiya Fergus, Paul Hamdan, Hani Liverpool John Moores Univ Byroom St Liverpool L3 3AF Merseyside England SUPELEC Dept Signal Proc & Elect Syst F-91190 Gif Sur Yvette France

ISBN: (纸本)9783319049601;9783319049595

Motion estimation procedures are employed in order to achieve reductions in the amount of resources required for data retention and therefore alleviate transmission demands of steaming digital video sequences across Information System infrastructures. The process comes at high computational expense, however there are a number of techniques in which attempt to expedite processing times for the compression of video streams by increasing the efficiency of resource utilisation through a minimisation of superfluous calculations incurred by imprudent video compression applications. A variety of fast, block-based matching algorithms have been developed to address such issues within the motion estimation process and to also exploit the assumptions made in regards to the behaviours exhibited by distortion distributions. This investigation will analyse a number of such methodologies through a literature review of their accompanying publications and will enable the development comparative analysis based on various performance indicators.

关键词： Motion estimation block matching algorithms video compression

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VLSI architectures for block matching algorithms using systolic arrays

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 1996年第1期6卷 67-73页

作者： Pan, SB Chae, SS Park, RH Department of Electronic Engineering Sogang University Seoul South Korea Signal Processing Lab Samsung Electronics Company Limited Suwon South Korea

In this paper, we investigate hardware implementation of block matching algorithms (BMA's) for motion estimation of moving sequences. Using systolic arrays, we propose VLSI architectures for the two-stage BMA and full search (FS) BMA. The two-stage BMA using integral projections reduces greatly. computational complexity with its performance comparable td that of the FS BMA. The proposed hardware architectures for the two-stage BMA and FS BMA are faster than the conventional hardware architectures with lower hardware complexity. Also, the proposed architecture of the first stage of the two-stage BMA is modeled in VHDL and simulated. Simulation results show the functional validity of the proposed architecture.

关键词： VLSI computational complexity digital signal processing chips image matching image sequences motion estimation systolic arrays video signal processing VHDL VLSI architectures block matching algorithms full search BMA hardware arc ARCHITECTURE Systolic algorithms image matching image sequences digital signal processing chips complexity classes block matching Very large scale integration motion estimation Video signal processing very high density lipoproteins

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A survey on video compression fast block matching algorithms

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NEUROCOMPUTING 2019年 335卷 215-237页

作者： Hussain, Abir Jaafar Ahmed, Zaynab Liverpool John Moores Univ Dept Comp Sci Appl Comp Res Grp Byrom St Liverpool L3 3AF Merseyside England Univ Baghdad Coll Sci Women Baghdad Iraq

Video compression is the process of reducing the amount of data required to represent digital video while preserving an acceptable video quality. Recent studies on video compression have focused on multimedia transmission, videophones, teleconferencing, high definition television, CD-ROM storage, etc. The idea of compression techniques is to remove the redundant information that exists in the video sequences. Motion compensation predictive coding is the main coding tool for removing temporal redundancy of video sequences and it typically accounts for 50-80% of video encoding complexity. This technique has been adopted by all of the existing International Video Coding Standards. It assumes that the current frame can be locally modelled as a translation of the reference frames. The practical and widely method used to carry out motion compensated prediction is block matching algorithm. In this method, video frames are divided into a set of non-overlapped macroblocks and compared with the search area in the reference frame in order to find the best matching macroblock. This will carry out displacement vectors that stipulate the movement of the macroblocks from one location to another in the reference frame. Checking all these locations is called Full Search, which provides the best result. However, this algorithm suffers from long computational time, which necessitates improvement. Several methods of Fast block matching algorithm are developed to reduce the computation complexity. This paper focuses on a survey for two video compression techniques: the first is called the lossless block matching algorithm process, in which the computational time required to determine the matching macroblock of the Full Search is decreased while the resolution of the predicted frames is the same as for the Full Search. The second is called lossy block matching algorithm process, which reduces the computational complexity effectively but the search result's quality is not the same as for

关键词： block matching algorithms Video compression MPEG

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Performance analysis of block matching motion estimation algorithms for HD videos with different search parameters

Performance analysis of block matching motion estimation alg...

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International Conference on Intelligent Systems Engineering (ICISE)

作者： Muzammil, Muhammad Khan, Zeshan Aslam Ali, Imdad Ullah, M. Obaid Int Islamic Univ Islamabad FET Dept Elect Engn Islamabad Pakistan Univ Engn & Technol Taxila FEEE Dept Elect Engn Taxila Pakistan

ISBN: (纸本)9781467387538

High Definition (HD) videos are the most widely used in HD television and mobile phones now a days for transmission and storage. Due to large data size, HD videos require efficient and robust video coding mechanism to enable real-time encoding. Numerous Motion Estimation (ME) algorithms are proposed to reduce the computational complexity of the coding process. In this paper, we present the performance analysis of some famous block matching ME algorithms (BMAs) for HD videos. Different performance measuring parameters are used to evaluate the performance of BMAs, like Peak Signal to Noise Ratio (PSNR), ME time, Mean Square Error (MSE). The simulation results show that the Adaptive Rood Pattern Search (ARPS) ME algorithm outperforms in term of MSE, PSNR and number of search points, for HD (720p) videos, over various search parameters. ARPS, Diamond Search (DS) and Flatted Hexagon Search (FHS) ME algorithms improve the PSNR from 32dB to 48dB for some video sequences, by increasing search range, whereas the number of search points also increased with the same parameter that causes to increased ME time and computational complexity.

关键词： Motion estimation HD video coding Adaptive rood pattern search Diamond search block matching algorithms

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block-matching algorithm based on harmony search optimization for motion estimation

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APPLIED INTELLIGENCE 2013年第1期39卷 165-183页

作者： Cuevas, Erik Univ Guadalajara Dept Elect CUCEI Guadalajara 44430 Jalisco Mexico

Motion estimation is one of the major problems in developing video coding applications. Among all motion estimation approaches, block-matching (BM) algorithms are the most popular methods due to their effectiveness and simplicity for both software and hardware implementations. A BM approach assumes that the movement of pixels within a defined region of the current frame can be modeled as a translation of pixels contained in the previous frame. In this procedure, the motion vector is obtained by minimizing a certain matching metric that is produced for the current frame over a determined search window from the previous frame. Unfortunately, the evaluation of such matching measurement is computationally expensive and represents the most consuming operation in the BM process. Therefore, BM motion estimation can be viewed as an optimization problem whose goal is to find the best-matching block within a search space. The simplest available BM method is the Full Search Algorithm (FSA) which finds the most accurate motion vector through an exhaustive computation of all the elements of the search space. Recently, several fast BM algorithms have been proposed to reduce the search positions by calculating only a fixed subset of motion vectors despite lowering its accuracy. On the other hand, the Harmony Search (HS) algorithm is a population-based optimization method that is inspired by the music improvisation process in which a musician searches for harmony and continues to polish the pitches to obtain a better harmony. In this paper, a new BM algorithm that combines HS with a fitness approximation model is proposed. The approach uses motion vectors belonging to the search window as potential solutions. A fitness function evaluates the matching quality of each motion vector candidate. In order to save computational time, the approach incorporates a fitness calculation strategy to decide which motion vectors can be only estimated or actually evaluated. Guided by the values of

关键词： Harmony search algorithm block matching algorithms Motion estimation Fitness approximation Video coding

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block matching algorithm for motion estimation based on Artificial Bee Colony (ABC)

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APPLIED SOFT COMPUTING 2013年第6期13卷 3047-3059页

作者： Cuevas, Erik Zaldivar, Daniel Perez-Cisneros, Marco Sossa, Humberto Osuna, Valentin Univ Guadalajara CUCEI Dept Elect Guadalajara 44430 Jal Mexico Ctr Invest Computac IPN Mexico City DF Mexico

block matching (BM) motion estimation plays a very important role in video coding. In a BM approach, image frames in a video sequence are divided into blocks. For each block in the current frame, the best matching block is identified inside a region of the previous frame, aiming to minimize the sum of absolute differences (SAD). Unfortunately, the SAD evaluation is computationally expensive and represents the most consuming operation in the BM process. Therefore, BM motion estimation can be approached as an optimization problem, where the goal is to find the best matching block within a search space. The simplest available BM method is the full search algorithm (FSA) which finds the most accurate motion vector through an exhaustive computation of SAD values for all elements of the search window. Recently, several fast BM algorithms have been proposed to reduce the number of SAD operations by calculating only a fixed subset of search locations at the price of poor accuracy. In this paper, a new algorithm based on Artificial Bee Colony (ABC) optimization is proposed to reduce the number of search locations in the BM process. In our algorithm, the computation of search locations is drastically reduced by considering a fitness calculation strategy which indicates when it is feasible to calculate or only estimate new search locations. Since the proposed algorithm does not consider any fixed search pattern or any other movement assumption as most of other BM approaches do, a high probability for finding the true minimum (accurate motion vector) is expected. Conducted simulations show that the proposed method achieves the best balance over other fast BM algorithms, in terms of both estimation accuracy and computational cost. (C) 2012 Elsevier B. V. All rights reserved.

关键词： Artificial Bee Colony block matching algorithms Motion estimation Fitness approximation

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block-matching algorithm for mitigating aliasing effects in undersampled image sequences

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OPTICAL ENGINEERING 2002年第2期41卷 359-369页

作者： Roggemann, MC Reynolds, WR Michigan Technol Univ Dept Elect Engn Houghton MI 49931 USA Signature Res Inc Calumet MI USA

Two fundamental motivations exist for designing remote sensing systems that are undersampled: (1) SNR considerations that motivate larger detectors to collect more photoevents per frame time and (2) the desire to maximize the field of view with a finite number of detectors. As a result, many remote sensing systems do not satisfy the Ny-quist sampling criterion, leading to measured images corrupted with a defect called aliasing. We describe a localized subpixel motion sensing algorithm that is used to properly place small blocks of the sequence of images in an upsampled space. Localized motion sensing enables dealiasing to be performed on image sequences with more complicated relative motion than simple translation. The presented results show improvements in both the edge response and subjective image quality. (C) 2002 Society of Photo-Optical Instrumentation Engineers.

关键词： image dealiasing block matching algorithms image reconstruction

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block-matching algorithm based on differential evolution for motion estimation

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2013年第1期26卷 488-498页

作者： Cuevas, Erik Zaldivar, Daniel Perez-Cisneros, Marco Oliva, Diego Univ Guadalajara CUCEI Dept Elect Guadalajara 44430 Jal Mexico Univ Complutense Madrid Dpto Ingn Software & Inteligencia Artificial Fac Informat E-28040 Madrid Spain

Motion estimation is one of the major problems in developing video coding applications. Among all motion estimation approaches, block-matching (BM) algorithms are the most popular methods due to their effectiveness and simplicity for both software and hardware implementations. A BM approach assumes that the movement of pixels within a defined region of the current frame (macro block, MB) can be modeled as a translation of pixels contained in the previous frame. In this procedure, the motion vector is obtained by minimizing the sum of absolute differences (SAD) produced by the MB of the current frame over a determined search window from the previous frame. The SAD evaluation is computationally expensive and represents the most consuming operation in the BM process. The most straightforward BM method is the full search algorithm (FSA), which finds the most accurate motion vector, exhaustively calculating the SAD values for all the elements of the search window. Over this decade, several fast BM algorithms have been proposed to reduce the number of SAD operations by calculating only a fixed subset of search locations at the cost of poor accuracy. In this paper, a new algorithm based on differential evolution (DE) is proposed to reduce the number of search locations in the BM process. To avoid computing several search locations, the algorithm estimates the SAD values (fitness) for some locations using the SAD values of previously calculated neighboring positions. As the proposed algorithm does not consider any fixed search pattern or any other different assumption, a high probability for finding the true minimum (accurate motion vector) is expected. In comparison with other fast BM algorithms, the proposed method deploys more accurate motion vectors, yet delivering competitive time rates. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： block matching algorithms Motion estimation Differential evolution Fitness approximation

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Efficient bat-inspired block matching algorithm with novel motion energy directional histograms for dynamic texture fast recognition

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MULTIMEDIA TOOLS AND APPLICATIONS 2024年第7期83卷 21633-21653页

作者： Bida, Ikram Aouat, Saliha Univ Sci & Technol Houari Boumediene USTHB Dept Comp Sci Algiers 16111 Algeria

Motion estimation is a crucial step in Dynamic Texture (DT) Motion-based recognition systems, as it directly affects the system's overall accuracy and computational proficiency. Whereas efficient motion estimation methods are pixel-based prioritizing recognition quality over computational complexity, this trade-off may not be acceptable in time-sensitive applications. Therefore, block matching algorithms (BMA) stand as potential alternative candidates, however, classic BMA often falls into local optimums ambushes resulting suboptimal solutions, particularly for complex motion videos such DT. In this paper, we propose a novel bat-inspired block matching approach for motion estimation to overcome the issue of falling into local optima. Our approach is inspired from the powerful search capacity of the bat algorithm seeking the best block within a search space;aiming accuracy improvement and a faster convergence. Afterwards, we extract motion features from the matched blocks fields to characterize the different DT videos. Two comprehensive sets of experiments were performed to validate the proposed approaches, Firstly the bat-inspired block motion estimation performance was compared against common algorithms on various standard video sequences. Moreover, the effectiveness of the introduced Dynamic Texture Recognition (DTR) system was demonstrated using well-known DT datasets, where comparative studies with state-of-art methods were presented. The results achieved a balance on computational speed and accuracy on multiple datasets.

关键词： Bat algorithm block matching algorithms Dynamic texture recognition Feature extraction Motion estimation PCA

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REAL-TIME block matching MOTION ESTIMATION ONTO GPGPU

REAL-TIME BLOCK MATCHING MOTION ESTIMATION ONTO GPGPU

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19th IEEE International Conference on Image Processing (ICIP)

作者： Monteiro, Eduarda Maule, Marilena Sampaio, Felipe Diniz, Claudio Zatt, Bruno Bampi, Sergio Univ Fed Rio Grande do Sul PGMICRO PPGC Inst Informat Oporto Alegre Portugal

ISBN: (纸本)9781467325332;9781467325349

This work presents an efficient method to map Motion Estimation (ME) algorithms onto General Purpose Graphic Processing Unit (GPGPU) architectures using CUDA programming model. Our method jointly exploits the massive parallelism available in current GPGPU devices and the parallelization potential of ME algorithms: Full Search (FS) and Diamond Search (DS). Our main goal is to evaluate the feasibility of achieving real-time high-definition video encoding performance running on GPUs. For comparison reasons, multi-core parallel and distributed versions of these algorithms were developed using OpenMP and MPI (Message Passing Interface) libraries, respectively. The CUDA-based solutions achieve the highest speed-up in comparison with OpenMP and MPI versions for both algorithms and, when compared to the state-of-the-art, our FS and DS solutions reach up to 18x and 11x speed-up, respectively.

关键词： Motion Estimation block matching algorithms GPU CUDA OpenMP MPI

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