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scalable video coding with robust mode selection

SIGNAL PROCESSING-IMAGE COMMUNICATION 2001年第8期16卷 725-732页

作者： Regunathan, S Zhang, R Rose, K Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

We propose to improve the packet loss resilience of scalable video coding. An algorithm for optimal coding mode selection for the base and enhancement layers is developed, which limits error propagation due to packet loss, while retaining compression efficiency. We first derive a method to estimate the overall decoder distortion, which includes the effects of quantization, packet loss and error concealment employed at the decoder. The estimate accounts for temporal and spatial error propagation due to motion compensated prediction, and computes the expected distortion precisely per pixel. The distortion estimate is incorporated within a rate-distortion framework to optimally select the coding mode as well as quantization step size for the macroblocks in each layer. Simulation results show substantial performance gains for both base and enhancement layers. (C) 2001 Elsevier Science B.V. All rights reserved.

关键词： video coding error resilience packet loss scalable coding source-channel coding error propagation error concealment

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scalable Image coding for Humans and Machines

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2022年 31卷 2739-2754页

作者： Choi, Hyomin Bajic, Ivan, V Simon Fraser Univ Sch Engn Sci Burnaby BC V5A 1S6 Canada

At present, and increasingly so in the future, much of the captured visual content will not be seen by humans. Instead, it will be used for automated machine vision analytics and may require occasional human viewing. Examples of such applications include traffic monitoring, visual surveillance, autonomous navigation, and industrial machine vision. To address such requirements, we develop an end-to-end learned image codec whose latent space is designed to support scalability from simpler to more complicated tasks. The simplest task is assigned to a subset of the latent space (the base layer), while more complicated tasks make use of additional subsets of the latent space, i.e., both the base and enhancement layer(s). For the experiments, we establish a 2-layer and a 3-layer model, each of which offers input reconstruction for human vision, plus machine vision task(s), and compare them with relevant benchmarks. The experiments show that our scalable codecs offer 37%-80% bitrate savings on machine vision tasks compared to best alternatives, while being comparable to state-of-the-art image codecs in terms of input reconstruction.

关键词： Task analysis Image reconstruction Image coding Scalability Object detection Multitasking Transforms Image compression deep neural network multitask network scalable coding latent-space scalability

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ON scalable coding OF HIDDEN MARKOV SOURCES

ON SCALABLE CODING OF HIDDEN MARKOV SOURCES

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Mehdi Salehifar Tejaswi Nanjundaswamy Kenneth Rose Department of Electrical and Computer Engineering University of California Santa Barbara CA 93106

ISBN: (纸本)9781479999897

While several real world signals, such as speech, image and sensor network data, are modeled as hidden Markov sources (HMS) for recognition and analysis applications, their typical compression exploits temporal correlations by modeling them as simple (non-hidden) Markov sources. However, the inherent hidden Markov nature of these sources implies that an observed sample depends, in fact, on all past observations, thus rendering simple Markov modeling suboptimal. Motivated by this realization, previous work from our lab derived a technique to optimally quantize and compress HMS. In this paper we build on, and considerably extend, these results to the problem of scalable coding of HMS. At the base layer, as proposed earlier, the approach tracks an estimate of the state probability distribution and adapts the encoder structure accordingly. At the enhancement layer, the state probability distribution is refined using available information from past enhancement layer reconstructed samples, and this refined estimate is further combined with quantization information from the base layer, to effectively characterize the probability density of the current sample conditioned on all available information. We update code parameters on the fly, at each observation, at both the encoder and the decoder and at both layers. Experimental results validate the superiority of the proposed approach with considerable gains over standard predictive coding employing a simple Markov model.

关键词： scalable coding Hidden Markov Sources

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SSSIC: Semantics-to-Signal scalable Image coding With Learned Structural Representations

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2021年 30卷 8939-8954页

作者： Yan, Ning Gao, Changsheng Liu, Dong Li, Houqiang Li, Li Wu, Feng Univ Sci & Technol China CAS Key Lab Technol Geospatial Informat Proc & Ap Hefei 230027 Peoples R China Kwai Inc Hangzhou 310018 Peoples R China

We address the requirement of image coding for joint human-machine vision, i.e., the decoded image serves both human observation and machine analysis/understanding. Previously, human vision and machine vision have been extensively studied by image (signal) compression and (image) feature compression, respectively. Recently, for joint human-machine vision, several studies have been devoted to joint compression of images and features, but the correlation between images and features is still unclear. We identify the deep network as a powerful toolkit for generating structural image representations. From the perspective of information theory, the deep features of an image naturally form an entropy decreasing series: a scalable bitstream is achieved by compressing the features backward from a deeper layer to a shallower layer until culminating with the image signal. Moreover, we can obtain learned representations by training the deep network for a given semantic analysis task or multiple tasks and acquire deep features that are related to semantics. With the learned structural representations, we propose SSSIC, a framework to obtain an embedded bitstream that can be either partially decoded for semantic analysis or fully decoded for human vision. We implement an exemplar SSSIC scheme using coarse-to-fine image classification as the driven semantic analysis task. We also extend the scheme for object detection and instance segmentation tasks. The experimental results demonstrate the effectiveness of the proposed SSSIC framework and establish that the exemplar scheme achieves higher compression efficiency than separate compression of images and features.

关键词： Image coding Feature extraction Task analysis Semantics Decoding Image representation Scalability Feature compression image compression image representation machine vision scalable coding

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Spatial scalable video coding using a combined subband-DCT approach

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2000年第7期10卷 1080-1087页

作者： Benzler, U Univ Hannover Inst Theoret Nachrichtentech & Informat Verarbeit Hannover Germany

A combined subband-DCT approach for spatial scalable video coding is presented. The high-resolution input signal is decomposed into four spatial subband signals. The low-frequency subband is used as the low-resolution signal and is separately coded in the base-layer bitstream, and the high-frequency subband signals are coded in the enhancement-layer bitstream, The low-resolution signal is reconstructed from the base-layer bitstream and the high-resolution signal is reconstructed using both the base- and the enhancement-layer bitstream, Similar to MPEG, DCT-based hybrid coding techniques are applied for the coding of the subband signals, but an improved motion-compensated prediction is used for the low-resolution signal. Additionally, SNR scalability is introduced to allow a flexible bit allocation for the base and the enhancement layer. Experimental results at a bit rate of 6 Mbit/s show that the reference coder MPEG-4 spatial scalable profile (SSP) leads to a loss of more than 2.2-dB peak signal-to-noise ratio (PSNR) compared with nonscalable MPEG-2 coding at the same bit rate, whereas the proposed combined subband-DCT scheme is able to achieve a decrease of less than 0.4 dB in PSNR.

关键词： scalable coding spatial scalability subband coding video coding

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On scalable Distributed coding of Correlated Sources

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2010年第5期58卷 2875-2883页

作者： Saxena, Ankur Rose, Kenneth Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

This paper considers the problem of scalable distributed coding of correlated sources that are communicated to a central unit, a setting typically encountered in sensor networks. As communication channel conditions may vary with time, it is often desirable to guarantee a base layer of coarse information during channel fades, as well as robustness to channel link (or sensor) failures. The main contribution is twofold. First, we consider the special case of multistage distributed coding, and show that naive combination of distributed coding with multistage coding yields poor rate-distortion performance, due to underlying conflicts between the objectives of these two coding methods. An appropriate system paradigm is developed, which allows such tradeoffs to be explicitly controlled. Next, we consider the unconstrained scalable distributed coding problem. Although a standard "Lloyd-style" distributed coder design algorithm is easily generalized to encompass scalable coding, the algorithm performance is heavily dependent on initialization and will virtually always converge to a poor local minimum. We propose an effective initialization scheme for such a system, which employs a properly designed multistage distributed coder. We present iterative design techniques and derive the necessary conditions for optimality for both multistage and unconstrained scalable distributed coding systems. Simulation results show substantial gains for the proposed multistage distributed coding system over naive extensions which incorporate scalability in a multistage distributed coding system. Moreover, the proposed overall scalable distributed coder design consistently and substantially outperforms the randomly initialized "Lloyd-style" scalable distributed coder design.

关键词： Distributed quantization multistage coding scalable coding sensor networks

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Secure service convergence based on scalable media coding

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TELECOMMUNICATION SYSTEMS 2010年第1期45卷 21-35页

作者： Lian, Shiguo France Telecom R&D Orange Labs Beijing Peoples R China

In multimedia services, security and privacy issues are urgent to be solved, such as the content security and service protection. To solve these issues, some means have been proposed, such as conditional access and digital rights management. However, for the latest application scenarios in convergent networks, there is still no solution. This paper focuses on the convergent multimedia broadcasting applications: the multimedia content, e.g., TV program, is encoded and packaged by the content provider, and is then transmitted to users through different communication networks, e.g., 3G network, DVB-H, ADSL, etc. Thus, the same multimedia content will be used for various services, i.e., mobile TV, Internet TV and home TV. Since different network channel support different bandwidths, the multimedia content should be transcoded before being transmitted through the networks. To protect the content and service in this application, we propose the content and service protection methods. In content protection, the content provider encrypts the scalable multimedia content with the manner denoted by Encryption Flag. The content distributor has no decryption keys, but can transcode the scalable content with the manner denoted by Layer Flag, and transmit the transcoded content to users. In service protection, the content provider combines the encryption key, Encryption Flag and the user right information, and transmits them, independent from the encrypted content, to certified users. At user side, the content is decrypted with the received key according to the Encryption Flag and Layer Flag. Thus, the content provider needs only to encrypt the content once, which can be transcoded by the content distributor in a secure manner and used for various networks. Additionally, the user rights need not to be changed when the service network is changed. Totally, the proposed scheme is secure and efficient for service convergence.

关键词： scalable coding scalable encryption Secure transcoding Service protection Secure interaction

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scalable Speech coding for IP Networks: Beyond iLBC

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IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING 2013年第11期21卷 2337-2345页

作者： Seto, Koji Ogunfunmi, Tokunbo Santa Clara Univ Dept Elect Engn Santa Clara CA 95053 USA

High quality speech at low bit rates makes code excited linear prediction (CELP) the dominant choice for a narrowband coding technique despite the susceptibility to packet loss. One of the few techniques which received attention after the introduction of CELP coding technique is the internet low bitrate codec (iLBC) because of inherent high robustness to packet loss. Addition of rate flexibility and scalability makes the iLBC an attractive choice for voice communication over IP networks. In this paper, performance improvement schemes of multi-rate iLBC and its scalable structure are proposed, and the proposed codec enhanced from the previous work is re-designed based on the subjective listening quality instead of the objective quality. In particular, perceptual weighting and the modified discrete cosine transform (MDCT) with short overlap in weighted signal domain are employed along with the improved packet loss concealment (PLC) algorithm. The subjective evaluation results show that the speech quality of the proposed codec is equivalent to that of state-of-the-art codec, G.718, under both a clean channel condition and lossy channel conditions. This result is significant considering that development of the proposed codec is still in early stage.

关键词： Discrete cosine transform (DCT) internet low bitrate codec (iLBC) packet loss scalable coding speech coding voice over Internet protocol (VoIP)

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A BACKWARD WAVELET REMESHER FOR LEVEL OF DETAIL CONTROL AND scalable coding

A BACKWARD WAVELET REMESHER FOR LEVEL OF DETAIL CONTROL AND ...

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IEEE International Conference on Image Processing

作者： Hao-Chiang Shao Wen-Liang Hwang Yung-Chang Chen Institute of Information Science Academia Sinica Department of Electrical Engineering National Tsing Hua Univesity

ISBN: (纸本)9781479957521

Multi-resolution and wavelet analysis have generated considerable interest in the field of mesh surface representation. In this paper, we propose a backward, coarse-to-fine framework that derives a semi-regular approximation of an original mesh, and demonstrate its effectiveness on level-of-detail and scalable coding applications. The framework is flexible and simple because the position of a new vertex at a finer resolution can be derived in a closed form, based on the affine combination of a subdivision scheme, the original mesh, and "new" information about the wavelet coefficients. We report the results of experiments on both applications;and also compare the scalable coding results with those of other methods.

关键词： affine transforms approximation theory image coding image representation image resolution level control wavelet transforms affine combination backward coarse-to-fine framework backward wavelet remesher analysis level of detail control mesh surface representation multiresolution analysis scalable coding application semiregular approximation subdivision scheme Encoding Interpolation Surface waves Vectors Wavelet transforms wavelet transforms Affine transformation scalable coding level control image representation Multiresolution analysis Approximation Theory image resolution surface waves image coding Interpolation

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Understanding perceptual distortion in MPEG scalable audio coding

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IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING 2005年第3期13卷 422-431页

作者： Creusere, CD New Mexico State Univ Klipsch Sch Elect & Comp Engn Las Cruces NM 88003 USA

In this paper, we study coding artifacts in MPEG-compressed scalable audio. Specifically, we consider the MPEG advanced audio coder (AAC) using bit slice scalable arithmetic coding (BSAC) as implemented in the MPEG-4 reference software. First we perform human subjective testing using the comparison category rating (CCR) approach, quantitatively comparing the performance of scalable BSAC with the nonscaled TwinVQ and AAC algorithms. This testing indicates that scalable BSAC performs very poorly relative to TwinVQ at the lowest bitrate considered (16 kb/s) largely because of an annoying and seemingly random mid-range tonal signal that is superimposed onto the desired output. In order to better understand and quantify the distortion introduced into compressed audio at low bit rates, we apply two analysis techniques: Reng bifrequency probing and time-frequency decomposition. Using Reng probing, we conclude that aliasing is most likely not the cause of the annoying tonal signal;instead, time-frequency or spectrogram analysis indicates that its cause is most likely suboptimal bit allocation. Finally, we describe the energy equalization quality metric (EEQM) for predicting the relative perceptual performance of the different coding algorithms and compare its predictive ability with that of ITU Recommendation ITU`-R BS.1387-1.

关键词： audio analysis audio coding audio quality metrics objective quality assessment perceptual distortion scalable coding

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