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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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Optimal coding of Generalized-Gaussian-Distributed Frequency Spectra for Low-Delay Audio Coder With Powered All-Pole Spectrum Estimation

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IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING 2015年第8期23卷 1309-1321页

作者： Sugiura, Ryosuke Kamamoto, Yutaka Harada, Noboru Kameoka, Hirokazu Moriya, Takehiro NTT Corp Yokohama Kanagawa 2430198 Japan

We present an optimal coding scheme that parameterizes the maximum-likelihood estimate of variance for frequency spectra belonging to the generalized Gaussian distribution, the distribution covering the Laplacian and the Gaussian. By slightly modifying the all-pole model of the conventional linear prediction (LP), we can estimate the variance with the same method as in LP, which has low computational costs. Experimental results show that incorporating the coding scheme in a state-of-the-art wide-band audio coder enhances its objective and subjective quality in a low-bit-rate and low-delay situation by increasing the compression efficiency. Thus, this coding scheme will be useful in applications like mobile communications, which requires highly efficient compression.

关键词： arithmetic coding audio compression generalized Gaussian distribution linear prediction low delay transform coded excitation

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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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Wavelet image coding using trellis coded space-frequency quantization

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IEEE SIGNAL PROCESSING LETTERS 1999年第7期6卷 158-161页

作者： Xiong, ZX Wu, XL Univ Hawaii Dept Elect Engn Honolulu HI 96822 USA Univ Western Ontario Dept Comp Sci London ON Canada

Recent progresses in wavelet image coding have brought the field into its maturity, Major developments in the process are rate-distortion (R-D) based wavelet packet transformation, zerotree quantization, subband classification and trellis-coded quantization, and sophisticated context modeling in entropy coding, Drawing from past experience and recent insights, we propose a new wavelet image coding technique with trellis coded space-frequency quantization (TCSFQ). TCSFQ aims to explore space-frequency characterizations of wavelet image representations via R-D optimized zerotree pruning, trellis-coded quantization, and context modeling in entropy coding. Experiments indicate that the TCSFQ coder achieves twice as much compression as the baseline JPEG coder does at the same peak signal to noise ratio (PSNR), making it better than all other coders described in the literature [1].

关键词： arithmetic coding context modeling space-frequency quantization trellis coded quantization wavelet transform

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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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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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Patch-Based Conditional Context coding of Stereo Disparity Images

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IEEE SIGNAL PROCESSING LETTERS 2014年第10期21卷 1220-1224页

作者： Tabus, Ioan Tampere Univ Technol Dept Signal Proc FIN-33101 Tampere Finland

This letter proposes a method for lossless coding the left disparity image, L, from a stereo disparity image pair (L, R), conditional on the right disparity image, R, by keeping track of the transformation of the constant patches from R to L. The disparities in R are used for predicting the disparities in L, and the locations of the pixels where the prediction is erroneous are encoded in a first stage, conditional on the patch-labels of R image, allowing the decoder to already reconstruct with certainty some elements of the L image, e.g., the disparity values at certain pixels and parts of the contours of left image patches. Second, the contours of the patches in L image that are still unknown after first stage are conditionally encoded using a mixed conditioning context: the usual causal current context from the contours of L and a noncausal context extracted from the contours in the correctly estimated part of L obtained in the first stage. The depth values in the patches of L image are finally encoded, if they are not already known from the prediction stage. The new algorithm, dubbed conditional crack-edge region value (C-CERV), is shown to perform significantly better than the non-conditional coding method CERV and than another existing conditional coding method, over the Middlebury corpus. C-CERV is shown to reach lossless compression ratios of 100-250 times for those images that have a high precision of the disparity map.

关键词： arithmetic coding context tree coding inter-coding lossless disparity image compression

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coding for a binary independent piecewise-identically-distributed source

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IEEE TRANSACTIONS ON INFORMATION THEORY 1996年第6期42卷 2210-2217页

作者： Willems, FMJ Dept. of Electr. Eng. Eindhoven Univ. of Technol. Netherlands

Two weighting procedures are presented for compaction of output sequences generated by binary independent sources whose unknown parameter may occasionally change, The resulting codes need no knowledge of the sequence length T, i.e., they are strongly sequential, and also the number of parameter changes is unrestricted, The additional-transition redundancy of the first method was shown to achieve the Merhav lower bound, i.e., log T bits per transition, For the second method we could prove that additional-transition redundancy is not more than 3/2 log T bits per transition, which is more than the Merhav bound;however, the storage and computational complexity of this method are also more interesting than those of the first method, Simulations show that the difference in redundancy performance between the two methods is negligible.

关键词： universal noiseless source coding independent piecewise-identically-distributed source nonstationary source transition pattern weighting arithmetic coding redundancy bounds

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Context modeling for near-lossless image coding

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IEEE SIGNAL PROCESSING LETTERS 2002年第3期9卷 77-80页

作者： Aiazzi, B Alparone, L Baronti, S CNR IROE Nello Carrara Res Inst Electromagnet Waves I-50127 Florence Italy Univ Florence Dept Elect & Telecommun I-50139 Florence Italy

This letter describes a context-based entropy coding suitable for any causal spatial differential pulse code modulation (DPCM) scheme performing lossless or near-lossless image coding. The proposed method is based on partitioning of prediction errors into homogeneous classes before arithmetic coding. A context function is measured on prediction errors lying within a two-dimensional (2-D) causal neighborhood, comprising the prediction support of the current pixel, as the root mean square (RMS) of residuals weighted by the reciprocal of their Euclidean distances. Its effectiveness is demonstrated in comparative experiments concerning both lossless and near-lossless coding. The proposed context coding/decoding is strictly real-time.

关键词： arithmetic coding DPCM entropy coding near-lossless coding statistical context modeling

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BINARY-UNCODED IMAGE AND VIDEO COMPRESSION USING SPIHT-ZTR coding

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INTERNATIONAL JOURNAL OF IMAGE AND GRAPHICS 2011年第3期11卷 415-437页

作者： Chia, Wai Chong Chew, Li Wern Ang, Li-Minn Seng, Kah Phooi Univ Nottingham Sch Elect & Elect Engn Selangor 43500 Malaysia

When the embedded zerotree wavelet (EZW) algorithm was first introduced by Shapiro, four types of symbols (zerotree (ZTR), isolated zero (IZ), positive (POS), and negative (NEG)) were used to represent the tree structure. An improved version of EZW, the set partitioning in hierarchical trees (SPIHT) algorithm was later proposed by Said and Pearlman. SPIHT removed the ZTR symbol, while keeping the other three symbols in a slightly different form. In the SPIHT algorithm, the coding of the parent node is isolated from the coding of its descendants in the tree structure. Therefore, it is no longer possible to encode the parent and its descendants with a single symbol. When both the parent and its descendants are insignificant (forming a degree-0 zerotree (ZTR)), it cannot be represented using a ZTR symbol. From our observation, the number of degree-0 ZTRs can occur very frequently not only in natural and synthesis images, but also in video sequences. Hence, the ZTR symbol is reintroduced into SPIHT in our proposed SPIHT-ZTR algorithm. In order to achieve this, the order of sending the output bits was modified to accommodate the use of ZTR symbol. Moreover, the significant offspring were also encoded using a slightly different method to further enhance the performance. The SPIHT-ZTR algorithm was evaluated on images and video sequences. From the simulation results, the performance of binary-uncoded SPIHT-ZTR is higher than binary-uncoded SPIHT and close to SPIHT with adaptive arithmetic coding.

关键词： SPIHT EZW image compression video compression arithmetic coding

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