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Dictionary learning based reconstruction for distributed compressed video sensing

JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2013年第8期24卷 1232-1242页

作者： Liu, Haixiao Song, Bin Qin, Hao Qiu, Zhiliang Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Peoples R China

distributed compressed video sensing (DCVS) is a framework that integrates both compressed sensing and distributed video coding characteristics to achieve a low-complexity video coding. However, how to design an efficient reconstruction by leveraging more realistic signal models that go beyond simple sparsity is still an open challenge. In this paper, we propose a novel "undersampled" correlation noise model to describe compressively sampled video signals, and present a maximum-likelihood dictionary learning based reconstruction algorithm for DCVS, in which both the correlation and sparsity constraints are included in a new probabilistic model. Moreover, the signal recovery in our algorithm is performed during the process of dictionary learning, instead of being employed as an independent task. Experimental results show that our proposal compares favorably with other existing methods, with 0.1-3.5 dB improvements in the average PSNR, and a 2-9 dB gain for non-key frames when key frames are subsampled at an increased rate. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Compressed sensing distributed video coding Dictionary learning Undersampled correlation noise model distributed compressed video sensing Sparse recovery Maximum likelihood Energy minimization

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distributed MULTI-HYPOTHESIS coding OF DEPTH MAPS USING TEXTURE MOTION INFORMATION AND OPTICAL FLOW

DISTRIBUTED MULTI-HYPOTHESIS CODING OF DEPTH MAPS USING TEXT...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Matteo Salmistraro Marco Zamarin Lars Lau Raket Soren Forchhammer DTU Fotonik Technical University of Denmark Department of Computer Science University of Copenhagen

ISBN: (纸本)9781479903573

distributed video coding (DVC) is a video coding paradigm allowing a shift of complexity from the encoder to the decoder. Depth maps are images enabling the calculation of the distance of an object from the camera, which can be used in multiview coding in order to generate virtual views, but also in single view coding for motion detection or image segmentation. In this work, we address the problem of depth map video DVC encoding in a single-view scenario. We exploit the motion of the corresponding texture video which is highly correlated with the depth maps. In order to extract the motion information, a block-based and an optical flow-based method are employed. Finally we fuse the proposed Side Information using a multi-hypothesis DVC decoder, which allows us to exploit the strengths of all the proposed methods at the same time.

关键词： distributed Source coding Depth Map coding Wyner-Ziv coding Optical Flow distributed video coding Optic Flow distributed source coding video coding digital video coding information maps STRUCTURE MAP Motion detection

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Wireless multicasting of video signals based on distributed compressed sensing

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SIGNAL PROCESSING-IMAGE COMMUNICATION 2014年第5期29卷 599-606页

作者： Wang, Anhong Zeng, Bing Chen, Hua Taiyuan Univ Sci & Technol Inst Digital Media & Commun Taiyuan Guangzhou Peoples R China Univ Elect Sci & Technol China Inst Image Proc Chengdu Sichuan Peoples R China

Multicasting of video signals over wireless networks has recently become a very popular application. Here, one major challenge is to accommodate heterogeneous users who have different channel characteristics and therefore will receive different noise-corrupted video packets of the same video source that is multicasted over the wireless network. This paper proposes a distributed compressed sensing based multicast scheme (DCS-cast), where a block-wise compressed sensing (BCS) is applied on video frames to obtain measurement data. The measurement data are then packed in an interleaved fashion and transmitted over OFDM channels. At the decoder side, users with different channel characteristics receive a certain number of packets and then reconstruct video frames by exploiting motion-based information. Due to the fact that the CS-measuring and interleaved packing together produce equally-important packets, users with good channel conditions will receive more packets so as to recover a better quality, which guarantees our DCS-cast scheme with a very graceful degradation rather than cliff effects. As compared to the benchmark SoftCast scheme, our DCS-cast is able to provide a better performance when some packets are lost during the transmission. (C) 2014 Elsevier B.V. All rights reserved.

关键词： video multicast Compressed sensing Graceful degradation distributed video coding

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Forging a Close Relationship with Multimedia Communities

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IEEE MULTIMEDIA 2014年第4期21卷 14-15页

作者： Zeng, Wenjun Liu, Zicheng Steinbach, Eckehard Univ Missouri Columbia MO 65211 USA Microsoft Res Asia Beijing Peoples R China Microsoft Res Redmond WA USA Tech Univ Munich D-80290 Munich Germany

In May 2014, the authors of the top 26 papers from the IEEE International Conference on Multimedia & Expo (ICME) 2014 were invited to submit extended versions of their papers to this fast track special issue. After a rigorous peer-review process, eight of those submissions were accepted for this special issue, now titled "Hot Topics in Multimedia Research." This is just the beginning of a close collaboration between MM and major multimedia conferences.

关键词： distributed video coding Multimedia Multimedia Research ICME Visual Analysis Object Tracking Image Quality Assessment Learning Algorithm Location Propagation Gaze Estimation

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Low Complexity Rate Estimators for Low Latency Wyner-Ziv video Decoders

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ENGINEERING LETTERS 2013年第1期21卷 1-9页

作者： Taieb, Mohamed Haj Chouinard, Jean-Yves Wang, Demin Univ Laval Dept Elect & Comp Engn Quebec City PQ G1V 0A8 Canada Commun Res Ctr Canada Adv Video Syst Ottawa ON K2H 8S2 Canada

distributed video coding is a video paradigm where most of the computational complexity can be transfered from video encoders to the decoders. This allows for video sequences transmission involving inexpensive encoders and powerful centralized decoders. Unfortunately, due to the typically numerous feedback requests and needed decoders run cycles, this often leads to unacceptably long decoding latencies. One approach to addressing the latency problem consists in estimating an initial number of parity bit chunks (INC) that are then sent at once to reduce the number of decoders run cycles. A practical implementation challenge is to properly estimate as accurately as possible the INC, that is, without neither underestimation nor overestimation. This paper proposes two INC estimation techniques based on the temporal correlation between successive Wyner-Ziv frames and on the correlation between the different bit-planes.

关键词： distributed video coding hybrid rate control feedback channel rate estimation

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A novel local smoothness constrained side-information frame generator

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2008年第2期E91A卷 692-694页

作者： Wang, Peng Wang, Jia Yu, Songyu Pang, Yuye Shanghai Jiao Tong Univ Dept EE Inst Image Commun & Informat Proc Shanghai Peoples R China

The quality of the Side-information frame (S frame) influences significantly the rate-distortion performance in the distributed video coding (DVC). In this letter, we propose an efficient Side-Information Frame Generator (SIFG). It considers smoothness constraints of both the motion vector field and spatial adjacent pixels. Simulation results show that the proposed techniques provide potential rate-distortion performance advantages. Besides, the fine visual quality of the S frame is obtained.

关键词： distributed video coding side-information frame motion vector field

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A review of the state-of-the-art distributed compressive video sensing architectures

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INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY 2014年第1-2期50卷 3-17页

作者： Imran, Noreen Seet, Boon-Chong Fong, A. C. M. Auckland Univ Technol Sch Engn Level 3Sci & Engn Bldg WS34 St Paul StCity Auckland 1010 New Zealand Auckland Univ Technol Sch Comp & Math Sci AUT TowerLevel 1 Wakefield St Entrance2-14 Auckland 1010 New Zealand

Low complexity video coding that provides efficient compression with reasonable reconstruction quality has been a desired requirement for resource-constrained video sensors in distributed vision-based sensing applications. In this paper, we present a review of the state-of-the-art codec architectures based on distributed compressive video sensing (DCVS), which is a relatively new video coding paradigm that integrates the techniques of distributed video coding (DVC) and compressive sensing (CS). The review includes a comparative discussion of several well-known DCVS architectures in literature with a focus on their functional aspects, and suggests a number of possible enhancements to the design of these architectures.

关键词： distributed video coding DVC compressive sensing/sampling CS distributed compressive video sensing DCVS DCVS architectures

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Quality and Complexity Controllable DVC Bitstream Organizer

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IEICE TRANSACTIONS ON COMMUNICATIONS 2012年第5期E95B卷 1894-1897页

作者： Kim, Chul Keun Cho, Yongwoo Park, Jongbin Suh, Doug Young Jeon, Byeungwoo Kyung Hee Univ Seoul South Korea Sungkyunkwan Univ Seoul South Korea

Applying distributed video coding (DVC) to mobile devices that have limited computation and power resources can be a very challenging problem due to its high-complexity decoding. To address this, this paper proposes a DVC bitstream organizer. The proposed DVC bitstream organizer reduces the complexity associated with repetitive channel decoding and SI generation in a flexible manner. It allows users to choose a means of minimizing the computational complexity of the DVC decoder according to their preferences and the device's resource limitations. An experiment shows that the proposed method increases decoding speeds by up to 25 times.

关键词： distributed video coding distributed source coding video compression video communication

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Residual Reconstruction Algorithm Based on Half-Pixel Multi-Hypothesis Prediction for distributed Compressive video Sensing

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INTERNATIONAL JOURNAL OF MOBILE COMPUTING AND MULTIMEDIA COMMUNICATIONS 2018年第4期9卷 16-33页

作者： Tong, Ying Chen, Rui Yang, Jie Wu, Minghu PLA Univ Sci & Technol Nanjing Jiangsu Peoples R China Nanjing Inst Technol Nanjing Jiangsu Peoples R China Hubei Univ Technol Wuhan Hubei Peoples R China

Compressed sensing (CS) provides a method to sample and reconstruct sparse signals far below the Nyquist sampling rate, which has great potential in image/video acquisition and processing. In order to fully exploit the spatial and temporal characteristics of video frame and the coherence between successive frames, we propose a half-pixel interpolation based residual reconstruction method for distributed compressive video sensing (DCVS). At the decoding end, half-pixel interpolation and bi-directional motion estimation helps refine the side information for joint decoding of the non-key-frames. We apply a multi-hypothesis based on residual reconstruction algorithms to reconstruct the non-key-frames. Performance analysis and simulation experiments show that the quality of side information generated by the proposed algorithm is increased by about 1.5dB, with video reconstruction quality increased 0.3 similar to 2dB in PSNR, when compared with prior works on DCVS.

关键词： Compressed Sensing distributed video coding Half-pixel Interpolation Motion Estimation Multi-hypothesis Prediction Side Information video Reconstruction

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Multi-view video codec using compressive sensing for wireless video sensor networks

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INTERNATIONAL JOURNAL OF MOBILE COMMUNICATIONS 2019年第6期17卷 727-745页

作者： Angayarkanni, Veeraputhiran Radha, S. Akshaya, V SSN Coll Engn Dept Elect & Commun Engn Chennai 603110 Tamil Nadu India

In monitoring applications, different views are needed to be captured by multi-view video sensor nodes for understanding the scene clearly. These multi-view sequences have large volume of redundant data which affects the storage, transmission, bandwidth and lifetime of wireless video sensor nodes. A low complex coding technique is required for addressing these issues and for processing multi-view sensor data. Hence, in this paper, a framework on CS-based multi-view video codec using frame approximation technique (CMVC-FAT) is proposed. Quantisation with entropy coding based on frame skipping is adopted for achieving efficient video compression. For better prediction of skipped frame at receiver, a frame approximation technique (FAT) algorithm is proposed. Simulation results reveal that CMVC-FAT framework outperforms the existing method with achievement of 86.5% reduction in time and bits. Also, it shows 83.75% reduction in transmission energy compared with raw frame.

关键词： multi-view encoding compressed sensing CS distributed video coding DVC frame approximation wireless video sensor networks WVSNs

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