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Multilayer reference frame motion estimation for video coding

SIGNAL IMAGE AND VIDEO PROCESSING 2015年第8期9卷 1851-1860页

作者： Paramkusam, A. V. Reddy, V. S. K. JNTUH Malla Reddy Coll Engn & Technol Elect & Commun Hyderabad Andhra Pradesh India

This paper proposes a new algorithm, multilayer motion estimation, based on the usage of a partial distortion measures with the objective of minimizing the overwhelming computational complexity of motion estimation. In order to make the computation of the partial distortion efficient, we build intermediate structures, which we have named as layers, from the reference frame using an overlapped hierarchical quad-tree structure. We have also proposed three types of search patterns to perform motion estimation on three layers. 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. Experimental results on a wide variety of video sequences show that the proposed algorithm outperforms the other state-of-the-art fast block matching algorithms while maintaining the motion prediction quality very close to the full-search algorithm.

关键词： block matching algorithm Motion estimation Multilayer motion estimation Fast search algorithm

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Optimized particle swarm optimization for faster and accurate video compression

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MULTIMEDIA TOOLS AND APPLICATIONS 2022年第16期81卷 23289-23310页

作者： Saikia, Monjul Choudhury, Hussain Ahmed Sinha, Nidul North Eastern Reg Inst Sci & Technol Dept Comp Sci & Engn Nirjuli 791109 Arunachal Prade India VIT Andhra Pradesh Dept CSE Amaravati India Natl Inst Technol Dept Elect Engn Silchar 788010 Assam India

The motion of objects in a video from one frame to another must be estimated quickly to speed up the video compression process. However, this should not deteriorate the visual appearance of the contents beyond the appropriate scope. This paper proposes improvisation of the fundamental Particle Swarm Optimization (PSO), known as Optimized PSO, to balance video compression quality and speed. The inertia portion of the particle velocity is modified dynamically to address the quality needed and broadly defines the movement to the global best place. To make the process quicker, additional stopping parameters, including predefined block distortion measurement, i.e., thresholds and the early identification of static macroblocks, are used to eradicate the movement estimation process for non-moving macroblocks. A small diamond search pattern is also implemented to investigate the impact of search patterns on optimizing the particulate swarm on the motion estimation process. The detailed simulations performed on different videos have proved that the proposed Optimized PSO versions for the block matching algorithm surpass several current modular block matching algorithms. It also produces even better estimation precision and speed than the possible particle swarm optimization-based motion estimation. The proposed versions of PSO-BMA referred to as Optimized PSOs have gained a speed up to 90-95% than that of FS with an acceptable compromise between the qualities of the reconstructed image.

关键词： block matching algorithm Motion estimation MAD Particle swarm optimization Cost function

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Moving objects detection in thermal scene videos using unsupervised Bayesian classifier with bootstrap Gaussian expectation maximization algorithm

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MULTIMEDIA TOOLS AND APPLICATIONS 2023年第2期83卷 6335-6350页

作者： Kerfa, Djoudi Natl Polytech Sch Oran Maurice Audin Ex Enset PB1523 El Mnaouar 31000 Algeria

In this paper, a new algorithm for moving object detection is proposed by using unsupervised Bayesian classifier with bootstrap Gaussian expectation maximization algorithm. It consists of the following steps: the first contains of classify and estimate the motion vectors between successive frames using the Star diamond search algorithm based on unsupervised Bayesian classifier with Gaussian Expectation of Maximization algorithm, this step serves also to detect the static and dynamic blocks. In the second step, the dynamic blocks are compensated with the white pixels value and the stationary are compensated by black pixels value. In the third step, the morphological opening and closing filters are used for refining the object detected. The proposed approach is trained and evaluated using available infrared (FLIR_ADAS_v2) dataset. The results demonstrate the effectiveness of the proposed method.

关键词： Infrared video sequences Moving object detection block matching algorithm Unsupervised bayesian classifier Gaussian expectation of maximization

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Predictive and distribution-oriented fast motion estimation for H.264/AVC

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JOURNAL OF REAL-TIME IMAGE PROCESSING 2014年第4期9卷 597-607页

作者： Pan, Zhaoqing Kwong, Sam Xu, Long Zhang, Yun Zhao, Tiesong City Univ Hong Kong Dept Comp Sci Hong Kong Hong Kong Peoples R China Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China

For fast motion estimation (ME) in video coding, many fast block matching ME algorithms are proposed. Among these algorithms, Unsymmetrical-cross Multi-grid-hexagon Search (UMHexagonS) algorithm can be regarded as a distinguished representative. However, the excellent rate-distortion (R-D) performance of UMHexagonS comes at the cost of relatively high computational complexity of the initial search point decision and the hybrid search pattern. To tackle this disadvantage, a new fast ME algorithm is proposed. An experiment is performed to analyze the best motion vectors (MVs) distribution in natural video sequences. Based on the correlations between spatial and temporal blocks as well as the asymmetrical distribution of the best MVs in natural video sequences, a small diamond search pattern and an asymmetrical cross search pattern are jointly employed to locate the best matching block. Experimental results demonstrate that when compared to recently improved UMHexagonS, the ME time can be reduced up to 38.70 % while with a quite similar R-D performance as UMHexagonS. When compared with the fast directional gradient descent search (FDGDS), the ME time can be reduced up to 12.23 %, while with a better R-D performance than FDGDS, 0.11 dB BDPSNR increase and 2.14 % BDBitrate decrease. Especially, the proposed algorithm can work well in video sequences with various motion activities and formats, and is more suitable for real-time application.

关键词： block matching algorithm Asymmetrical cross search pattern Motion estimation H.264/AVC Video coding

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HIERARCHICAL VARIABLE block SIZE MOTION ESTIMATION TECHNIQUE FOR MOTION SEQUENCE CODING

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OPTICAL ENGINEERING 1994年第8期33卷 2553-2561页

作者： KIM, JW LEE, SU AUTOMAT & SYST RES INST SEOUL 151742SOUTH KOREA

Motion-compensated coding, which exploits the temporal redundancies in the moving images, is one of the most popular techniques currently used. Recently, a variable block size (VBS) motion estimation technique has been proposed to improve the performance of the motion-compensated transform coding (MCTC). This technique allows larger blocks to be used when smaller blocks provide little gain, saving the bit rates especially for areas containing more complex motion. However, there have been few efforts to investigate an efficient VBS motion structure for reducing the motion vector coding rates further. Hence, a new VBS motion estimation technique based on a hierarchical structure is proposed that improves the motion vector encoding efficiency and reduces the number of motion vectors to be transmitted as well. Specifically, the gain/cost motion estimation technique with the selective motion prediction is utilized for the topmost level motion vector search, exploiting the redundancies among the neighboring motion vectors. Also, a restricted search with respect to the topmost level motion vector enables more flexible and efficient motion vector encoding for the remaining lower level blocks. Intensive simulations on several moving image sequences show that the MCTC employing the VBS motion estimation provides a performance improvement of 0.7 to 1.0 dB, in terms of peak SNR, compared with the fixed block size motion estimation.

关键词： MOTION COMPENSATED CODING VARIABLE block SIZE MOTION ESTIMATION HIERARCHICAL VARIABLE block SIZE block matching algorithm MOTION VECTOR CODING

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Recurrent pattern matching based stereo image coding using linear predictors

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MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING 2017年第4期28卷 1393-1416页

作者： Lucas, Luis F. R. Rodrigues, Nuno M. M. Pagliari, Carla L. da Silva, Eduardo A. B. de Faria, Sergio M. M. Univ Fed Rio de Janeiro PEE COPPE DEL Poli BR-21941972 Rio De Janeiro Brazil Inst Telecomunicacoes P-2411901 Leiria Portugal ESTG Inst Politecn Leiria P-2411901 Leiria Portugal Inst Mil Engn DEE BR-22290270 Rio De Janeiro Brazil

The Multidimensional Multiscale Parser (MMP) is a pattern-matching-based generic image encoding solution which has been investigated earlier for the compression of stereo images with successful results. While first MMP-based proposals for stereo image coding employed dictionary-based techniques for disparity compensation, posterior developments have demonstrated the advantage of using predictive methods. In this paper, we focus on recent investigations on the use of predictive methods in the MMP algorithm and propose a new prediction framework for efficient stereo image coding. This framework comprises an advanced intra directional prediction model and a new linear predictive scheme for efficient disparity compensation. The linear prediction model is the main novelty of this work, combining adaptive linear models estimated by least-squares algorithm with fixed linear models provided by the block-matching algorithm. The performance of the proposed intra prediction and disparity compensation methods when applied in an MMP encoder has been evaluated experimentally. Comparisons with the current stereo image coding standards showed that the proposed MMP algorithm significantly outperforms the Stereo High Profile of H.264/AVC standard. In addition, it presents a competitive performance relative to the MV-HEVC standard. These results also suggest that current stereo image coding standards may benefit from the proposed linear prediction scheme for disparity compensation, as an extension to the omnipresent block-matching solution.

关键词： Stereo image coding Pattern matching Disparity compensation Linear prediction Least-squares prediction block matching algorithm

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A novel fast search motion estimation boosted by multilayer concept

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MULTIMEDIA TOOLS AND APPLICATIONS 2016年第4期75卷 2169-2188页

作者： Paramkusam, A. V. Reddy, V. S. K. JNTUH Malla Reddy Coll Engn Elect & Commun Hyderabad Andhra Pradesh India

Most of the fast search motion estimation algorithms reduce the computational cost of motion estimation (ME) greatly by checking only a few search points inside the search area by using full distortion measure. This paper proposes multi-layer motion estimation (MME) which employs partial distortion as its distortion measure to reduce the number of computations involved in each search point instead of reducing the number of search points. The MME, first, constructs the layers from the reference frame so as to facilitate the calculation of partial distortion measures on the layers. Later, it searches motion vectors by computing the partial distortion measures on the layers. A layer is an image which is derived from the reference frame such that the summation of a block of pixels in the reference frame determines the point of a layer. It has been noticed on different video sequences that many motion vectors on the layers are the same as those searched on the reference frame. 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.

关键词： block matching algorithm Motion estimation Multi layer motion estimation Fast search algorithm

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Reduction of dot crawl and rainbow artifacts in the NTSC video

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IEEE TRANSACTIONS ON CONSUMER ELECTRONICS 2007年第2期53卷 740-748页

作者： Lee, Ji Won Lee, Hyun-Seung Park, Rae-Hong Kim, Sunghee Sogang Univ Dept Elect Engn Seoul 100611 South Korea Samsung Elect Co Ltd Digital Media Res & Dev Ctr Suwon 442742 Kyunggido South Korea

In the encoder of the national television system committee (NTSC) system, a composite video burst signal (CVBS) is generated using the luminance (Y) signal and the quadrature amplitude modulation (QAM) modulated chrominance (C) signal. In the decoder, it is important that the CVBS be accurately separated into luminance and chrominance signals by a Y/C separation filter. Otherwise, various artifacts, such as dot crawl, rainbow effect, and color bleeding, appear in a decoded video, degrading the quality of the decoded video. In addition, modern high-definition television (HDTV) system suffers from outdated analog decoding artifacts when HDTV compression techniques were applied to the not ideally decoded former standard-definition format video images. This paper proposes artifact reduction methods of dot crawl and rainbow effect using the characteristics of the CVBS video. The proposed artifact reduction algorithms use two successive frames, in which the decoded video images are divided into not moving (stationary) and moving regions. The stationary regions are filtered by a temporal filter, whereas the moving regions are further classified into three subdivided regions of different types of artifacts to apply them into temporal or spatial filters because inappropriately temporally filtered moving region delivers jitters on the edge. In the proposed algorithms, considering characteristics of the NTSC decoded image, a block matching algorithm based on 4x4 non-overlapping blocks is used for motion estimation and compensation. Computer simulations with various simulated and real videos containing NTSC artifacts show the effectiveness of the proposed artifact reduction methods.

关键词： artifact reduction block matching algorithm comb filter CVBS displaced frame difference dot crawl field frame interlaced motion compensation motion estimation NTSC artifact NTSC artifact decision map NTSC system QAM rainbow effect spatial filtering temporal filtering

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A three-dimensional instrumentation VLSI processor based on a concurrent memory-access scheme

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IEICE TRANSACTIONS ON ELECTRONICS 1997年第11期E80C卷 1491-1498页

作者： Lee, S Hariyama, M Kameyama, M Graduate School of Information Sciences Tohoku University Sendai-shi 980-8579 Japan

Three-dimensional (3-D) instrumentation using an image sequence is a promising instrumentation method for intelligent systems in which accurate 3-D information is required. However, real-time instrumentation is difficult since much computation lime and a large memory bandwidth are required. In this paper, a 3-D instrumentation VLSI processor with a concurrent memory-access scheme is proposed. To reduce the access time, frequently used data are stored in a cache register array and are concurrently transferred to processing elements using simple interconnections to the 8-nearest neighbor registers. Based on a row and column memory access pattern, we propose a diagonally interleaved frame memory by which pixel Values of a row and column are stored across memory modules. Based on the concurrent memory-access scheme, a 40 GOPS vprocessor is designed and the delay time for the instrumentation is estimated to be 42 ms for a 256x256 images.

关键词： 3-D instrumentation epipolar constraint block matching algorithm special-purpose VLSI processor memory interleaving

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Image mosaic with relaxed motion

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SIGNAL IMAGE AND VIDEO PROCESSING 2012年第4期6卷 647-667页

作者： Fang, Xianyong Zhu, Jiejie Luo, Bin Anhui Univ Sch Comp Sci & Technol Key Lab Intelligent Comp & Signal Proc MOE Hefei Anhui Peoples R China Univ Cent Florida Comp Vis Lab Orlando FL 32816 USA

We propose a novel method to stitch images with relatively large roll or pitch called relaxed motion, which defies most existing mosaic algorithms. Our approach adopts a multi-resolution strategy, which combines the merits of both feature-based and intensity-based methods. The main contribution is a robust motion estimation procedure which integrates an adaptive multi-scale block matching algorithm called TV-BMA, a low contrast filter and a RANSAC motion rectification to jointly refine motion and feature matches. Based on TV - L (1) model, the proposed TV-BMA works on the coarsest layer to find a robust initial displacement field as the initial motion for source images. This motion estimation method can generate robust correspondences for further processing. In the subsequent camera calibration step, we also present two stable methods to estimate the camera matrix. To estimate the focal length, we combine the golden section search and the simplex method based on the angle invariance of feature vectors;to estimate the rotation matrix, we introduce a subspace trust region method, which matches features based on the rotation invariance. Extensive experiments show that our approach leads to improved accuracy and robustness for stitching images with relaxed motion.

关键词： Image mosaic Relaxed motion block matching algorithm Low contrast filter TV - L-1 model Angle invariance Rotation invariance

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