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Adaptive quantization and fast error-resilient entropy coding for image transmission

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 1998年第4期8卷 411-421页

作者： Chandramouli, R Ranganathan, N Ramadoss, SJ Univ S Florida Dept Comp Sci & Engn Ctr Microelect Res Tampa FL 33620 USA

Recently, there has been an outburst of research in image and video compression for transmission over noisy channels, Channel matched source quantizer design has gained prominence, Further, the presence of variable-length codes in compression standards like the JPEG and the MPEG has made the problem more interesting. error resilient entropy coding (EREC) has emerged as a new and effective method to combat catastrophic loss in the received signal due to burst and random errors. In this paper, we propose a new channel-matched adaptive quantizer for JPEG image compression. A slow, frequency-nonselective Rayleigh fading channel model is assumed. The optimal quantizer that matches the human visibility threshold and the channel bit-error rate is derived. Further, a new fast error-resilient entropy code (FEREC) that exploits the statistics of the JPEG compressed data is proposed, The proposed FEREC algorithm is shown to be almost twice as fast as EREC in encoding the data, and hence the error resilience capability is also observed to be significantly better. On an average, a 5% decrease in the number of significantly corrupted received image blocks is observed with FEREC, Upto a 2-dB improvement in the peak Signal-to-noise ratio of the received image is also achieved.

关键词： adaptive quantization error-resilient coding fading image compression JPEG

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error resilient VIDEO coding USING HYBRID HIERARCHICAL B PICTURES

ERROR RESILIENT VIDEO CODING USING HYBRID HIERARCHICAL B PIC...

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19th IEEE International Conference on Image Processing (ICIP)

作者： Tsai, Wen-Jiin Liu, Wan-Han Natl Chiao Tung Univ Hsinchu Taiwan

ISBN: (纸本)9781467325332;9781467325349

In this paper, a hybrid model based on hierarchical B picture structure is proposed to improve error concealment effects when there is a whole-frame loss. The model combines two hierarchical B-picture coding structures such that key-frames, reference B frames, or even non-reference B frames have buddy frames to serve as their data recovery frames when they are lost. With buddy frames, the distance between a lost frame and its recovering frame can be substantially reduced and thus error concealment performance can be improved with little bit-rate redundancy.

关键词： Hybrid model hierarchical B pictures error concealment error-resilient coding

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error-resilient VIDEO coding USING MULTIPLE REFERENCE FRAMES

ERROR-RESILIENT VIDEO CODING USING MULTIPLE REFERENCE FRAMES

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20th IEEE International Conference on Image Processing (ICIP)

作者： Tsai, Wen-Jiin Sun, Yu-Chen Natl Chiao Tung Univ Dept Comp Sci Hsinchu Taiwan

ISBN: (纸本)9781479923410

An error-resilient scheme based on multiple reference frames is proposed, which employs error-resilient frames (ER-frame) as part of reference frames and adopts a rate-distortion optimized (RDO) technique to choose the blocks referring to ER-frames. To reduce the computational cost, two techniques are further proposed. Experimental results show that adopting ER-frames enhances error-resilient performance;using RDO makes the scheme adaptive to various packet loss rates and video sequences;and applying time reduction techniques reduces computational cost significantly with neglectable performance loss.

关键词： error-resilient coding rate-distortion optimization multiple reference frames

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error-resilient VIDEO coding USING MULTIPLE REFERENCE FRAMES

ERROR-RESILIENT VIDEO CODING USING MULTIPLE REFERENCE FRAMES

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IEEE International Conference on Image Processing

作者： Wen-Jiin Tsai Yu-Chen Sun Department of Computer Science National Chiao Tung University Taiwan R.O.C.

ISBN: (纸本)9781479923427

关键词： error-resilient coding rate-distortion optimization multiple reference frames REFERENCE FRAMES Rate distortion remote data object Videotapes Packet loss Frame Video sequences FRAMES

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error-resilient video streaming over wireless networks using combined scalable coding and multiple-description coding

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SIGNAL PROCESSING-IMAGE COMMUNICATION 2007年第4期22卷 403-420页

作者： Chen, Chih-Ming Chen, Chien-Min Lin, Chia-Wen Chen, Yung-Chang Natl Tsing Hua Univ Dept Elect Engn Hsinchu 300 Taiwan Chunghwa Telecom Co Ltd Telecommun Labs Tao Yuan 326 Taiwan

In this paper, we propose a novel error-resilient coding technique, namely, multiple-description fine granularity scalability (MD-FGS) coding, to enhance error resiliency while retaining good temporal prediction efficiency for video transport over error-prone networks, especially for wireless channels. The proposed MD-FGS coding scheme is based on a combination of FGS and modified MD scalar quantization (MDSQ), named Base-MDSQ, in which partial prediction is utilized to control drifting error. We also propose an adaptive soft handoff algorithm to effectively mitigate video quality degradation caused by transient channel switching when a mobile client roams in wireless local area networks (WLANs). The handoff algorithm utilizes a channel estimator to decide which channels should be used for delivering video. Experimental results show that the proposed method effectively mitigates error propagation due to packet loss while maintaining good coding efficiency. (C) 2007 Elsevier B.V. All rights reserved.

关键词： video streaming error-resilient coding transcoding scalable coding path diversity multiple-description coding channel handoff

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JOINT TEXTURE AND DEPTH MAP coding FOR error-resilient 3-D VIDEO TRANSMISSION 24

JOINT TEXTURE AND DEPTH MAP CODING FOR ERROR-RESILIENT 3-D V...

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24th IEEE International Conference on Image Processing (ICIP)

作者： Gao, Pan Xiang, Wei Rahaman, D. M. Motiur Paul, Manoranjan Nanjing Univ Aeronaut & Astronaut Coll Comp Sci & Technol Nanjing Jiangsu Peoples R China James Cook Univ Coll Sci & Engn Townsville Qld Australia Charles Sturt Univ Sch Comp & Math Bathurst NSW Australia

ISBN: (纸本)9781509021758

This paper addresses the problem of error-resilient source coding for 3-D video transmission over packet-loss networks. The proposed approach jointly optimizes the texture coding mode and the depth coding mode for each macroblock in the reference views. Firstly, a distortion model is developed to capture the effect of the texture distortion and depth distortion on the synthesized view. Then, joint optimization of texture and depth coding modes is derived based upon an operational rate-distortion framework using Lagrange multiplier method. In particular, a dual trellis-based algorithm is introduced in order to overcome the macroblock interdependencies of texture and depth map in the optimization procedure. Simulation results demonstrate that significant and consistent gains can be achieved over currently used techniques.

关键词： Texture coding mode depth coding mode error-resilient coding 3-D video transmission

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ESTIMATION OF END-TO-END DISTORTION OF VIRTUAL VIEW FOR error-resilient DEPTH MAP coding

ESTIMATION OF END-TO-END DISTORTION OF VIRTUAL VIEW FOR ERRO...

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20th IEEE International Conference on Image Processing (ICIP)

作者： Gao, Min Fan, Xiaopeng Zhao, Debin Jiang, Feng Gao, Wen Harbin Inst Technol Dept Comp Sci & Technol Harbin 150006 Peoples R China

ISBN: (纸本)9781479923410

In this paper, we propose to estimate the end-to-end distortion of virtual view for error-resilient depth map coding by analyzing the view-rendering process. The end-to- end distortion is estimated according to the expectation of depth distortion. The expectation of depth distortion is estimated based on the error-propagated distortion from the reference frame, which is calculated recursively for each pixel by considering the source characteristics, channel condition and error concealment method. The error-propagated distortion in terms of each frame is updated after the frame is encoded, which is used for the subsequent frames. Experimental results demonstrate that the proposed algorithm achieves substantial and consistent gains in comparison with the random intra updating method and the conventional rate-distortion method for error-resilient depth map coding.

关键词： Depth map coding error-resilient coding end-to-end distortion virtual view

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SoundSpring: Loss-resilient Audio Transceiver With Dual-Functional Masked Language Modeling

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2025年第4期43卷 1308-1322页

作者： Yao, Shengshi Dai, Jincheng Qin, Xiaoqi Wang, Sixian Wang, Siye Niu, Kai Zhang, Ping Beijing Univ Posts & Telecommun Key Lab Universal Wireless Commun Minist Educ Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China

In this paper, we propose "SoundSpring", a cutting-edge error-resilient audio transceiver that marries the robustness benefits of joint source-channel coding (JSCC) while also being compatible with current digital communication systems. Unlike recent deep JSCC transceivers, which learn to directly map audio signals to analog channel-input symbols via neural networks, our SoundSpring adopts the layered architecture that delineates audio compression from digital coded transmission, but it sufficiently exploits the impressive in-context predictive capabilities of large language (foundation) models. Integrated with the casual-order mask learning strategy, our single model operates on the latent feature domain and serve dual-functionalities: as efficient audio compressors at the transmitter and as effective mechanisms for packet loss concealment at the receiver. By jointly optimizing towards both audio compression efficiency and transmission error resiliency, we show that mask-learned language models are indeed powerful contextual predictors, and our dual-functional compression and concealment framework offers fresh perspectives on the application of foundation language models in audio communication. Through extensive experimental evaluations, we establish that SoundSpring apparently outperforms contemporary audio transmission systems in terms of signal fidelity metrics and perceptual quality scores. These new findings not only advocate for the practical deployment of SoundSpring in learning-based audio communication systems but also inspire the development of future audio semantic transceivers.

关键词： Transceivers Codecs Resilience Context modeling Packet loss Decoding Audio coding Robustness Receivers Propagation losses Semantic-aware transceiver audio communication error-resilient coding masked language models

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error/Erasure-resilient and Complexity-Constrained Zero-Delay Distributed coding for Large-Scale Sensor Networks

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ACM TRANSACTIONS ON SENSOR NETWORKS 2015年第2期11卷 35-35页

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

There has been considerable interest in distributed source coding (DSC) in recent years, primarily due to its potential contributions to low-power sensor networks. However, two major obstacles pose an existential threat to practical deployment of such techniques: the exponential growth of decoding complexity with network size and coding rates and the critical requirement of resilience to bit errors and erasures, given the severe channel conditions in many wireless sensor network applications. This article proposes a novel, unified approach for large-scale, error/erasure-resilient DSC that incorporates an optimally designed, nearest neighbor classifier-based decoding framework, where the design explicitly controls performance versus decoding complexity. Motivated by the highly nonconvex nature of the cost function, we present a deterministic annealing-based optimization algorithm for the joint design of the system parameters, which further enhances the performance over the greedy iterative descent technique. Simulation results on both synthetic and real sensor network data provide strong evidence for performance gains compared to other state-of-the-art techniques and may open the door to practical deployment of DSC in large sensor networks. Moreover, the framework provides a principled way to naturally scale to large networks while constraining decoder complexity, thereby enabling performance gains that increase with network size.

关键词： Algorithms Theory Experimentation Distributed source-channel coding large-scale sensor networks error-resilient coding complexity-constrained decoding

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ESTIMATION OF END-TO-END DISTORTION OF VIRTUAL VIEW FOR error-resilient DEPTH MAP coding

ESTIMATION OF END-TO-END DISTORTION OF VIRTUAL VIEW FOR ERRO...

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IEEE International Conference on Image Processing

作者： Min Gao Xiaopeng Fan Debin Zhao Feng Jiang Wen Gao Dept. of Computer Science and Technology Harbin Institute of Technology Harbin China

ISBN: (纸本)9781479923427

In this paper, we propose to estimate the end-to-end distortion of virtual view for error-resilient depth map coding by analyzing the view-rendering process. The end-to-end distortion is estimated according to the expectation of depth distortion. The expectation of depth distortion is estimated based on the error-propagated distortion from the reference frame, which is calculated recursively for each pixel by considering the source characteristics, channel condition and error concealment method. The error-propagated distortion in terms of each frame is updated after the frame is encoded, which is used for the subsequent frames. Experimental results demonstrate that the proposed algorithm achieves substantial and consistent gains in comparison with the random intra updating method and the conventional rate-distortion method for error-resilient depth map coding.

关键词： Depth map coding error-resilient coding end-to-end distortion virtual view

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