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Compressing Vehicle Trajectory Data Using Hybrid coding With Kinematic Motion Prediction

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2024年第6期25卷 5389-5401页

作者： Xu, Lipeng Wu, Zhizhou Wang, Yinhai Tang, Jinjun Liang, Yunyi Xinjiang Univ Sch Mech Engn Urumqi 830049 Peoples R China Univ Washington Dept Civil & Environm Engn Seattle WA 98195 USA Cent South Univ Sch Transportat Engn Changsha 410017 Peoples R China Cent South Univ Sch Traff & Transportat Engn Changsha Peoples R China Univ Shanghai Sci & Technol Business Sch Shanghai 200093 Peoples R China

This paper proposes a methodology combining Long-Short-Term-Memory (LSTM)-assisted kinematic motion prediction with a hybrid coding algorithm for compressing the trajectory data of Connected Autonomous Vehicles (CAVs). The vehicle locations after the first two time steps are predicted based on the vehicle positions at the first two time steps and the kinematic equation. The vehicle velocities and accelerations are predicted based on the vehicle locations and LSTM. The hybrid coding algorithm integrates differential coding, Binary Coded Decimal (BCD) coding and arithmetic coding. Differential coding converts the original data into the difference between the original data and the predicted data. Since the length of the original data is large but the difference between it and predicted data is small, the required space for storing the data can be greatly reduced. BCD coding converts subsequences of different lengths to the subsequences with the same length so that the original information can be correctly reproduced after decompression. arithmetic coding expresses the information in small space by converting the character sequence into a decimal between 0 and 1. The proposed algorithm is evaluated on the Next Generation Simulation Trajectory dataset. The experiment results show that the compression ratio and compression rate obtained by the proposed algorithm are respectively higher and lower than those obtained by the baseline algorithms. Also, the sum of compression time, decompression time and transmission time associated with the proposed algorithm is less than that associated with most baseline algorithms and transmission without compression.

关键词： Trajectory Prediction algorithms Logic gates Kinematics Channel coding arithmetic Data compression Trajectory data compression connected autonomous vehicles long short-term memory differential coding BCD coding arithmetic coding

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Image coding based on wavelet transform and uniform scalar dead zone quantizer

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SIGNAL PROCESSING-IMAGE COMMUNICATION 2006年第7期21卷 562-572页

作者： Chen, Jianhua Zhang, Yufeng Shi, Xinling Yunnan Univ Dept Elect Engn Kunming 650091 Peoples R China

In this paper, a new wavelet transform image coding algorithm is presented. The discrete wavelet transform (DWT) is applied to the original image. The DWT coefficients are firstly quantized with a uniform scalar dead zone quantizer. Then the quantized coefficients are decomposed into four symbol streams: a binary significance map symbol stream, a binary sign stream, a position of the most significant bit (PMSB) symbol stream and a residual bit stream. An adaptive arithmetic coder with different context models is employed for the entropy coding of these symbol streams. Experimental results show that the compression performance of the proposed coding algorithm is competitive to other wavelet-based image coding algorithms reported in the literature. (C) 2006 Elsevier B.V. All rights reserved.

关键词： wavelet image coding quantization arithmetic coding

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Vector SPIHT for embedded wavelet video and image coding

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2003年第3期13卷 231-246页

作者： Mukherjee, D Mitra, SK Univ Calif Santa Barbara Dept Elect & Comp Engn Image Proc Lab Santa Barbara CA 93106 USA

The set partitioning in hierarchical trees (SPIHT) approach for still-image compression proposed by Said and Pearlman is one of the most efficient embedded monochrome image compression schemes known to date. The algorithm relies on a very efficient scanning and bit-allocation scheme for quantizing the coefficients obtained by a wavelet decomposition of an image. In this paper, we adopt this approach to scan groups (vectors) of wavelet coefficients, and use successive refinement vector quantization (VQ) techniques with staggered bit-allocation to quantize the groups at once. The scheme is named vector SPIHT (VSPIHT). We present discussions on possible models for the distributions of the coefficient vectors, and show how trained classified tree-multistage VQ techniques can be used to efficiently quantize them. Extensive coding results comparing VSPIHT to scalar SPIHT in the mean-squared-error sense, are presented for monochrome images. VSPIHT is found to yield superior performance for most images, especially those with high detail content. The method is also applied to color video coding, where a partially scalable bitstream is generated. We present the coding results on QCIF sequences as compared against H.263.

关键词： arithmetic coding EZW scalable SPIHT vector quantization video coding wavelets zerotree

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coding theory

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WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS 2009年第3期1卷 261-270页

作者： Stine, Robert A. Univ Penn Dept Stat Philadelphia PA 19104 USA

coding theory is a portion of information theory concerned with the explicit representation of data as a sequence of symbols, usually a sequence of bits. The entropy of a probability distribution measures the information content of data, giving a lower bound on the number of bits necessary to encode data. Source coding also defines a measure, the divergence, of the cost of using a suboptimal representation. Channel coding describes representations that maximize the rate at which information can be communicated through a noisy medium. Important applications of coding theory include data compression, signal processing, and the comparison of statistical models. (C) 2009 John Wiley & Sons, Inc.

关键词： arithmetic coding divergence entropy mutual information universal code

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BLOCK TRUNCATION coding WITH ENTROPY coding

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IEEE TRANSACTIONS ON COMMUNICATIONS 1995年第2-4期43卷 1677-1685页

作者： FRANTI, P NEVALAINEN, O Department of Computer Science University of Turku Turku Finland

Block Truncation coding (ETC) is a simple and fast image compression algorithm which achieves constant bit rate of 2.0 bits per pixel, The method is however suboptimal. In the present paper we propose a modification of ETC in which the compression ratio will be improved by coding the quantization data and the bit plane by arithmetic coding with an adaptive modelling scheme. The results compare favorable with other ETC variants. The bit rate for test image Lena is 1.53 bits per pixel with the mean square error of 16.51.

关键词： compression ratio constant bit rate (CBR) pixel image compression algorithm Entropy coding arithmetic coding Mean square error Block truncation coding

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Joint lossless-source and channel coding using automatic repeat request

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IEEE TRANSACTIONS ON COMMUNICATIONS 1999年第7期47卷 953-955页

作者： Elmasry, GF New Jersey Inst Technol Dept Elect & Comp Engn Newark NJ 07102 USA

The susceptibility of arithmetic coding to errors is utilized for channel error recovery using an automatic repeat request (ARQ) scheme. The presented scheme optimizes the tradeoff between the redundancy added to overcome channel errors and detection capability. With this approach, the type of error pattern introduced by the channel does not affect the receiver's detection capability. This scheme is suitable for transmitting long files over low bit error rate channels, and it provides the assurance of reconstructing the original data, free from catastrophic errors.

关键词： Signal encoding Error detection Error correction Bit error rate Data compression Decoding Probability Codes (symbols) Joint lossless source coding Channel coding Automatic repeat request error model Automatic repeat request error correction detection capability Data compression DEcoding arithmetic coding Signal encoding Channel coding Error detection

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Significance map pruning and other enhancements to SPIHT image coding algorithm

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SIGNAL PROCESSING-IMAGE COMMUNICATION 2003年第9期18卷 769-785页

作者： Bayazit, U ISIK Univ Dept Elect Engn TR-34398 Istanbul Turkey

This paper proposes several enhancements to the Set Partitioning in Hierarchical Trees (SPIHT) image coding algorithm without changing the original algorithm's general skeleton. First and foremost, a method for significance map pruning based on a rate-distortion criterion is introduced. Specifically, the (Type A) sets of wavelet coefficients with small ratios of estimated distortion reduction to estimated rate contribution are deemed insignificant and effectively pruned. Even though determining such sets requires the computational complexity of the encoder to increase considerably with respect to the original SPIHT encoder, the original SPIHT decoder may still be used to decode the generated bitstream with a low computational complexity. The paper also proposes three low complexity enhancements by more sophisticated use of the adaptive arithmetic coder. Simulation results demonstrate that all these enhancements yield modest compression gains at moderate to high rates. (C) 2003 Elsevier B.V. All rights reserved.

关键词： image coding wavelet SPIHT pruning arithmetic coding

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Context-based entropy coding in AVS video coding standard

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SIGNAL PROCESSING-IMAGE COMMUNICATION 2009年第4期24卷 263-276页

作者： Zhang, Li Wang, Qiang Zhang, Ning Zhao, Debin Wu, Xiaolin Gao, Wen Chinese Acad Sci Inst Comp Technol Key Lab Intelligent Informat Proc Beijing Peoples R China Harbin Inst Technol Dept Comp Sci & Engn Harbin 150006 Peoples R China McMaster Univ Dept Elect & Comp Engn Hamilton ON L8S 4L8 Canada Peking Univ Sch Elect Engn & Comp Sci Inst Digital Media Beijing 100871 Peoples R China

In this paper, two context-based entropy coding schemes for AVS Part-2 video coding standard are presented. One is Context-based 2D Variable Length coding (C2DVLC) as a low complexity entropy coding scheme for AVS Part-2 Jizhun profile. C2DVLC uses Multiple 2D-VLC tables to exploit the statistical features of DCT coefficients for higher coding efficiency. Exponential-Golomb codes are applied in C2DVLC to code the pairs of the run-length of zero coefficients and the non-zero coefficients for lower storage requirement. The other is Context-based Binary arithmetic coding (CBAC) as an enhanced entropy coding scheme for AVS Part-2 Jiaqiang profile. CBAC utilizes all previously coded coefficient magnitudes in a DCT block for context modeling. This enables adaptive arithmetic coding to exploit the redundancy of the high-order Markov process in DCT domain with a few contexts. In addition, a context weighting technique is used to further improve CBAC's coding efficiency. Moreover, CBAC is designed to be compatible to C2DVLC in coding elements which simplifies the implementations. The experimental results demonstrate that both C2DVLC and CBAC can achieve comparable or even slightly higher coding performance when compared to Context-Adaptive Variable Length coding (CAVLC) in H.264/AVC baseline profile and Context-Based Adaptive Binary arithmetic coding (CABAC) in H.264/AVC main profile respectively. (C) 2009 Elsevier B.V. All rights reserved.

关键词： AVS DCT video coding Entropy coding Context modeling Variable length coding arithmetic coding

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An Innovative Chain coding Technique for Compression Based on the Concept of Biological Reproduction: An Agent-Based Modeling Approach

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IEEE INTERNET OF THINGS JOURNAL 2019年第6期6卷 9308-9315页

作者： Dhou, Khaldoon Cruzen, Christopher Drury Univ Breech Sch Business Adm Springfield MO 65802 USA Univ Missouri Dept Math & Comp Sci St Louis MO 63121 USA

The accelerated progress of the Internet of Things (IoT) and the nature of its heterogeneous parts cause difficulties in transferring data between different components. These rapid developments make it crucial to investigate new techniques to reduce the size of the data transmitted over the channels. In this paper, we develop an original chain code for compression that is inspired by the concept of biological reproduction. The new chain code is implemented via developing an agent-based modeling simulation consisting of rabbits, carrots, and paths for the rabbits to wander. The environment in the model represents an actual bi-level image consisting of zeros and ones. In our "biological reproduction" method, a rabbit starts wandering in the virtual world to consume carrots, while its movements are tracked and recorded by the algorithm. Each rabbit's movement is recorded based on its previous movement. Additionally, after a rabbit consumes a certain number of carrots, it gains energy and therefore reproduces another rabbit, which continues to work on the same image, and so on. Accordingly, more rabbits simultaneously work on different parts of an image, which makes the biological reproduction method advantageous over many other classical image processing approaches. The experimental results showed that the current method could outperform well-known image compression techniques, including JBIG family algorithms, on all the images used for testing.

关键词： Agent-based modeling arithmetic coding bi-level images bio-inspired computing biological reproduction chain code Internet of Things (IoT) lossless compression virtual worlds

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Interval algorithm for homophonic coding

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IEEE TRANSACTIONS ON INFORMATION THEORY 2001年第3期47卷 1021-1031页

作者： Hoshi, M Han, TS Univ Electrocommun Grad Sch Informat Syst Chofu Tokyo 1828585 Japan

It is shown that the idea of the successive refinement of interval partitions, which plays the key role in the interval algorithm for random number generation by Han and Hoshi, is also applicable to the homophonic coding. An interval algorithm for homophonic coding is introduced which produces an independent and identically distributed (i.i.d.) sequence with probability p, Lower and upper bounds for the expected codeword length are given. Based on this, an interval algorithm for fixed-to-variable homophonic coding is established, The expected codeword length per source letter converges to H(X) / H(p) in probability as the block length tends to infinity, where H(X) is the entropy rate of the source X. The algorithm is asymptotically optimal. An algorithm for fixed-to-fixed homophonic coding is also established. The decoding error probability tends to zero as the block length tends to infinity. Homophonic coding with cost is generally considered. The expected cost of the codeword per source letter converges to (c) over bar (X) / H (p) in probability as the block length tends to infinity, where (c) over bar denotes the verage cost of a source letter. The main contribution of this paper can be regarded as a novel application of Elias' coding technique to homophonic coding. Intrinsic relations among these algorithms, the interval algorithm for random number generation and the arithmetic code are also discussed.

关键词： arithmetic coding cost coding Elias coding homophonic coding interval algorithm random number generation

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