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Confidentiality of a selectively encrypted H.264 coded video bit-stream

JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2014年第2期25卷 487-498页

作者： Asghar, Mamoona N. Ghanbari, Mohammed Fleury, Martin Reed, Martin J. Univ Essex Sch CSEE Colchester CO4 3SQ Essex England

It is an assumption that selective encryption does not strongly protect confidentiality owing to the partial visibility of some video data. This is because, though encryption keys may be difficult to derive, an enhanced version of selectively encrypted video sequence might be found from knowledge of the unencrypted parts of the sequence. An efficient selective encryption method for syntax elements of H.264 encoded video was recently proposed at the entropy coding stage of an H.264 encoder. Using this recent scheme as an example, the purpose of this paper is a comprehensive cryptanalysis of selectively encrypted H.264 bit-streams to contradict the previous assumption that selective encryption is vulnerable. The novel cryptanalysis methods presented in this paper analyze the ability of an attacker to improve the quality of the encrypted video stream to make it watchable. The conclusion is drawn that if the syntax elements for selective encryption are chosen using statistical and structural characteristics of the video, then the selective encryption method is secure. The cryptanalysis is performed by taking into account the probability distribution of syntax elements within the video sequence, the relationship of syntax elements with linear regression analysis and the probability of successfully attacking them in order to enhance the visual quality. The results demonstrate the preservation of distorted video quality even after considering many possible attacks on: the whole video sequence;each video frame;and on small video segments known as slices. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Confidentiality Cryptanalysis entropy coding Guessing attacks Perceptual attacks Probability analysis Selective encryption Syntax elements

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Low-Complexity Rate-Distortion Optimization for HEVC Encoders

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IEEE TRANSACTIONS ON BROADCASTING 2021年第3期67卷 721-735页

作者： Huang, Bo Chen, Zhifeng Su, Kaixiong Chen, Jian Ling, Nam Beijing Kuaishou Technol Ltd Beijing Peoples R China Fuzhou Univ Dept Phys & Informat Engn Fuzhou 350108 Peoples R China Santa Clara Univ Dept Comp Engn Santa Clara CA 95053 USA

Typical high efficiency video coding (HEVC) encoders use rate-distortion optimization (RDO) to select the best coding parameters among numerous candidates to achieve high compression efficiency. However, calculating the rate-distortion cost for each coding parameter entails high computational complexity, which limits the real-time application of these encoders. In this study, time-consuming processes, such as reconstruction and entropy coding, are removed during the calculation of the full RD cost to reduce the complexity of the encoder. Instead, RD costs are estimated for transformed coefficients by using the RD cost model, which is made up of a distortion model based on the distribution features of the transformed coefficients, a residual rate model based on the characteristics of the entropy coding module, and a simple and convenient header rate model. In addition to the full RD cost, typical encoders also adopt fast RD cost, which is composed of the sum of absolute transform differences (SATD) and header bit. To further reduce encoding complexity, three simplified SATD (SSATD) methods based on DCT and DST features are proposed to serve as substitutes for SATD in fast RD cost, thus reducing the computational complexity of SATD calculation. Experimental results show that 35.53%, 14.57%, and 14.37% of coding time can be reduced respectively under AI, RA and LDP configurations with negligible RD performance loss when applying the proposed RD cost model and the SSATD methods to HM16.7. Besides, the proposed methods also can reduce 4%-9% of encoding time and exhibits the same RD performance as state-of-the-art methods.

关键词： Distortion Bit rate Computational modeling Estimation entropy coding Rate-distortion Optimization Rate-distortion cost HEVC low-complexity SATD

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Enhancement of an image compression algorithm by pre- and post-filtering

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OPTICAL ENGINEERING 2001年第2期40卷 193-199页

作者： Hadar, O Stern, A Koresh, R Ben Gurion Univ Negev Dept Commun Syst Engn IL-84105 Beer Sheva Israel Ben Gurion Univ Negev Dept Elect & Comp Engn IL-84105 Beer Sheva Israel

We present an algorithm that improves the overall performance of compression algorithms by applying low-pass filtering before the compression process and inverse filtering after decompression. Prefiltering images prior to encoding removes high spatial frequencies from the original image, thus increasing the compression ratio of the encoder. The image degradation caused by the filter together with the nonlinear transformation of a typical compression algorithm reduces the entropy of the original image, thus increasing the compression ratio. In addition to improving the compression ratio, the suggested scheme reduces the blocking effect that is common to block-based compression algorithms, such as the Joint Picture Experts Group (JPEG). (C) Poor society of Photo-Optical Instrumentation Engineers.

关键词： image compression entropy coding image filtering image restoration

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Using Compression to Discover Interesting Behaviours in a Hybrid Braitenberg Vehicle

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IEEE ACCESS 2021年 9卷 11316-11327页

作者： Ahmed, Nadim Teahan, William J. Bangor Univ Sch Comp Sci & Elect Engn Bangor LL57 1UT Gwynedd Wales

The simple rules that govern the interactions between the different components of a complex system often lead to interesting behaviours that are unexpected. The experiments described in this paper involved creating a variation of a traditional Braitenberg Vehicle, by placing sensors on ten different possible locations on a simulated vehicle, and incorporating an obstacle avoidance behaviour using a subsumption-like architecture, which resulted in different unusual and unexpected behaviours being produced. The vehicle was allowed to explore a simulated environment which contained a single bright light in the centre with walls on the border. By using a novel combination of the Prediction by Partial Matching compression algorithm and k-means clustering, interesting emergent behaviours were effectively discovered within a search space of over 10,000 simulations produced from a simple interaction of light and proximity sensors on a vehicle and a single light source. The clustering algorithm discovered five distinct behaviours: circling and spiralling behaviours;interesting behaviours creating intricate rose petal-like structures;behaviours that create simple rose petal-like structures;behaviours with large movements and low complexity;and behaviours with less movement. The novel algorithm demonstrated in this paper has useful potential in the science of complex systems and modelling to help expedite the systematic exploration of a substantial search space of simulations in order to discover interesting behaviours.

关键词： entropy coding robot motion Braitenberg vehicles subsumption architecture prediction by partial matching

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EUICN: An Efficient Underwater Image Compression Network

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2024年第7期34卷 6474-6488页

作者： Li, Mengyao Shen, Liquan Hua, Xia Tian, Zhaoyi Shanghai Univ Sch Commun & Informat Engn Shanghai 200444 Peoples R China Shanghai Univ Key Lab Specialty Fiber Opt & Opt Access Networks Joint Int Res Lab Specialty Fiber Opt & Adv Commun Shanghai 200444 Peoples R China

Thriving ocean applications bring explosive growth of underwater images (UWIs), which urgently demand to be compressed efficiently for transmission in the narrow underwater acoustic channel. However, existing image compression networks achieve suboptimal performance on UWIs. More efficient UWI compression can be achieved by utilizing characteristics of UWIs: (1) Within an UWI, the details distribution is associated with the underwater imaging transmission map (T-map);(2) Different UWIs have higher correlation than terrestrial images because they often present gauzy-covered indistinct appearance and share some universal ocean objects that widely appear in different underwater scenes. This paper fully exploits the two characteristics in terms of quantization and entropy coding, two key components of image compression network. Specifically, we propose an efficient underwater image compression network (EUICN) including underwater T-map-based quantization (UTMQ) and mixture entropy coding (MEC). In which, UTMQ extracts the imaging features from T-map, which are integrated with latent features by a novel dual-spatial attention module (DSAM) to generate a feature reserved mask, adaptively reserving reasonable numbers of features for different regions. For more efficient entropy coding, MEC is designed, which includes three correlation information extraction modules ( $i.e.$ , hyperprior, local and novel universal information) and a probability prediction module. Especially, the universal information extraction module utilizes a comprehensive underwater feature dictionary, which covers various universal ocean objects, to match with latent features to select the universal correlation features. After that, the probability prediction module is designed to consolidate the hyperprior, local, and universal information to predict more accurate probability of latent features. Extensive experiments show that our EUICN achieves better performance than SOTA learned and conventional co

关键词： Image coding Imaging Feature extraction Correlation Quantization (signal) entropy coding Oceans Underwater image compression underwater imaging model convolution neural network quantization entropy model

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On joint information embedding and lossy compression in the presence of a stationary memoryless attack channel

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IEEE TRANSACTIONS ON INFORMATION THEORY 2005年第9期51卷 3166-3175页

作者： Maor, A Merhav, N Technion Israel Inst Technol Dept Elect Engn IL-32000 Haifa Israel

We consider the problem of optimum joint public information embedding and lossy compression with respect to a fidelity criterion. The decompressed composite sequence (stego-text) is distorted by a stationary memoryless attack, resulting in a forgery which in turn is fed into the decoder, whose task is to retrieve the embedded information. The goal of this paper is to characterize the maximum achievable embedding rate R-e (the embedding capacity C-e) as a function of the compression (composite) rate R-c and the allowed average distortion level Delta, such that the average probability of error in decoding of the embedded message can be made arbitrarily small for sufficiently large block length. We characterize the embedding capacity and demonstrate how it can be approached in principle. We also provide a single-letter expression of the minimum achievable composite rate as a function of R-e and Delta below which there exists no reliable embedding scheme.

关键词： entropy coding information embedding information hiding lossless/lossy compression rate-distortion theory watermarking

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Optimal entropy-constrained scalar quantization of a uniform source

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IEEE TRANSACTIONS ON INFORMATION THEORY 2000年第7期46卷 2704-2711页

作者： György, A Linder, T Queens Univ Dept Math & Stat Kingston ON K7L 3N6 Canada Tech Univ Budapest Dept Comp Sci & Informat Theory Budapest Hungary

Optimal scalar quantization subject to an entropy constraint is studied for a wide class of difference distortion measures including rth-power distortions with r > 0. It is proved that if the source is uniformly distributed over an interval, then for any entropy constraint R (in nats), an optimal quantizer has N = [e(R)] interval cells such that N - 1 cells have equal length d and orle cell has length c less than or equal to d. The cell lengths are uniquely determined by the requirement that the entropy constraint is satisfied with equality. Based on this result, a parametric representation of the minimum achievable distortion D-h(R) as a function of the entropy constraint R is obtained for a uniform source. The D-h(R) curve turns out to be nonconvex in general. Moreover, for the squared-error distortion it is shown that D-h(R) is a piecewise-concave function, and that a scaler quantizer achieving the loser convex hull of D-h(R) exists only at rates R = log N, where N is a positive integer.

关键词： constrained optimization difference distortion measures entropy coding scalar quantization uniform source

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Three-dimensional PAC video codec for wireless data transmission

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2000年第8期10卷 1455-1470页

作者： Wen, KA Chen, AY Lan, YJ Lin, JL Lin, CH Natl Chiao Tung Univ Inst Elect Engn Hsinchu Taiwan Philips Res E Asia Taipei Taiwan

A newly derived algorithm called three-dimensional polynomial approximation coding (3DPAC) is being utilized in the applications of wireless video transmission. After combining the spatial and temporal domain, the video data is organized in a cube form, which has the features of processing parallelism and great compression ratio. Such a very low bit-rate video codec is able to support the wireless data transmission with a bit rate lower than 9.6 kbits/s, The system architecture will be presented and an experimental demonstration is also shown. For a video sequence of 176 x 144 frame size, PSNR up to 35 dB maybe obtained under 6.5 kbits/s transmission rate.

关键词： combined source coding and channel modulation entropy coding multimedia communication variable bit rate coding videocoding

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Context-based, adaptive, lossless image coding

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IEEE TRANSACTIONS ON COMMUNICATIONS 1997年第4期45卷 437-444页

作者： Wu, XL Memon, N NO ILLINOIS UNIV DEPT COMP SCIDE KALBIL 60115

We propose a context-based, adaptive, lossless image codec (CALIC). The codec obtains higher lossless compression of continuous-tone images than other lossless image coding techniques in the literature, This high coding efficiency is accomplished with relatively low time and space complexities, CALIC puts heavy emphasis on image data modeling. A unique feature of CALIC is the use of a large number of modeling contexts (states) to condition a nonlinear predictor and adapt the predictor to varying source statistics, The nonlinear predictor can correct itself via an error feedback mechanism by learning from its mistakes under a given context in the past. In this learning process, CALIC estimates only the expectation of prediction errors conditioned on a large number of different contexts rather than estimating a large number of conditional error probabilities, The former estimation technique can afford a large number of modeling contexts without suffering from the context dilution problem of insufficient counting statistics as in the latter approach, nor from excessive memory use, The low time and space complexities are also attributed to efficient techniques for forming and quantizing modeling contexts.

关键词： adaptive prediction entropy coding image compression statistical context modeling

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A CHIP SET FOR LOSSLESS IMAGE COMPRESSION

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IEEE JOURNAL OF SOLID-STATE CIRCUITS 1991年第3期26卷 237-244页

作者： SHAH, IA AKIWUMIASSANI, O JOHNSON, B N AMER PHILIPS LIGHTING CORP PHILIPS LABRES STAFFBRIARCLIFF MANORNY 10510

This chip set performs the S-transform [1], [2] image decomposition and the Lempel-Ziv [L-Z] [5], [6], [9] type of entropy coding. The compression ratio achieved by the system exceeds 2:1 for 10-b 2000 x 2000-pixel computed radiographs [3] at an average rate of 7.5 Mpixels/s [4]. The paper presents the transform and coding algorithms, the main architectural features of the chips, and outlines some performance specifications.

关键词： Image coding entropy coding Laboratories Pixel Radiography Decorrelation Karhunen-Loeve transforms Circuits Image decomposition Digital images

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