• Journal of Korea Multimedia Society
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• v.20 no.5
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• pp.731-739
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• 2017

Distributed compressed video sensing (DCVS) is a framework that integrates both compressed sensing and distributed video coding characteristics to achieve a low complexity video sampling. In DCVS schemes, motion estimation & motion compensation is employed at the decoder side, similarly to distributed video coding (DVC), for a low-complex encoder. However, since a simple BCS-SPL algorithm is applied to a residual arising from motion estimation and compensation in conventional MC-BCS-SPL (motion compensated block compressed sensing with smoothed projected Landweber) scheme, the reconstructed visual qualities are severly degraded in Wyner-Ziv (WZ) frames. Furthermore, the scheme takes lots of iteration to reconstruct WZ frames. In this paper, the conventional MC-BCS-SPL algorithm is improved to be operated in more effective way in WZ frames. That is, first, the proposed algorithm calculates a correlation coefficient between two reference key frames and, then, by selecting adaptively the reference frame, the residual reconstruction in pixel domain is performed to the conventional BCS-SPL scheme. Experimental results show that the proposed algorithm achieves significantly better visual qualities than conventional MC-BCS-SPL algorithm, while resulting in the significant reduction of the decoding time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.7
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• pp.1355-1363
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• 2017

Recently, distributed compressed video sensing (DCVS) has been actively studied in order to achieve a low complexity video encoder by integrating both compressed sensing and distributed video coding characteristics. Conventionally, a motion compensated block compressed sensing with smoothed projected Landweber (MC-BCS-SPL) has been considered as an effective scheme of DCVS with all compressed sensing frames pursuing the simplest sampling. In this scheme, video frames are separately classified into key frames and WZ frames. However, when reconstructing WZ frame with conventional MC-BCS-SPL scheme at the decoder side, the visual qualities are poor for temporally active video sequences. In this paper, to overcome the drawbacks of the conventional scheme, an enhanced MC-BCS-SPL algorithm is proposed, which corrects the initial image with reference to the key frame using a high correlation between adjacent key frames. The proposed scheme is analyzed with respect to GOP (Group of Pictures) structuring method. Experimental results show that the proposed method performs better than conventional MC-BCS-SPL in rate-distortion.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.2
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• pp.27-34
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• 2017

For The Purpose of Pursuing the Simplest Sampling, a Motion Compensated Block Compressed Sensing with Smoothed Projected Landweber (MC-BCS-SPL) has been Studied for an Effective Scheme of Distributed Compressive Video Sensing with all Compressed Sensing (CS) Frames. However, Conventional MC-BCS-SPL Scheme is Very Simple and so it Does not Provide Good Visual Qualities in Reconstructed Wyner-Ziv (WZ) Frames. In this Paper, the Conventional Scheme of MC-BCS-SPL is Modified to Provide Better Visual Qualities in WZ Frames. That is, the Proposed Agorithm is Designed in such a way that the Reference Frame may be Adaptively Selected Based on the Temporal Correlation Between Successive Frames. Several Experimental Results show that the Proposed Algorithm Provides Better Visual Qualities than Conventional Algorithm.

• Journal of Internet Technology
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• v.21 no.1
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• pp.203-219
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• 2020

Compressed video sensing (CVS) is one of the 5G application of compressed sensing (CS) to video coding. Block-based residual reconstruction is used in CVS to explore temporal redundancy in videos. However, most current studies on CVS focus on random measurements without quantization, and thus they are not suitable for practical applications. In this study, an efficient ratecontrol scheme combining measurement rate and quantization for residual reconstruction in CVS is proposed. The quantization effects on CS measurements and recovery for video signals are first analyzed. Based on this, a mathematical relationship between quantitative distortion (QD), sampling rate (SR), and the quantization parameter (QP) is derived. Moreover, a novel distortion model that exhibits the relationship between QD, SR, and QP is presented, if statistical independency between the QD and the CS reconstruction distortion is assumed. Then, using this model, a rate-distortion (RD) optimized rate allocation algorithm is proposed, whereby it is possible to derive the values of SR and QP that maximize visual quality according to the available channel bandwidth.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.6
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• pp.47-58
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• 2018

Recently, remote sensing video applications have become increasingly important in many wireless networks. Distributed compressive video sensing (DCVS) framework in these applications has been studied to reduce encoding complexity and to simultaneously capture and compress video data. Specially, a motion compensated block compressed sensing with smoothed projected Landweber (MC-BCS-SPL) has been actively researched for one useful algorithm of DCVS schemes, However, conventional MC-BCS-SPL schemes do not provide good visual qualities in reconstructed Wyner-Ziv (WZ) frames. In this paper, the conventional schemes of MC-BCS-SPL are described and then upgraded to provide better visual qualities in WZ frames by introducing reliability estimate between adjacent key frames and by constructing efficiently motion-compensated interpolated frames. Through experimental results, it is shown that the proposed algorithm is effective in providing better visual qualities than conventional algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.2
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• pp.366-385
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• 2013

In this paper, we propose a compressed sensing (CS) based Wyner-Ziv (WZ) codec using motion-aligned auto regressive model (MAAR) based side information (SI) extrapolation to improve the compression performance of low-delay distributed video coding (DVC). In the CS based WZ codec, the WZ frame is divided into small blocks and CS measurements of each block are acquired at the encoder, and a specific CS reconstruction algorithm is proposed to correct errors in the SI using CS measurements at the decoder. In order to generate high quality SI, a MAAR model is introduced to improve the inaccurate motion field in auto regressive (AR) model, and the Tikhonov regularization on MAAR coefficients and overlapped block based interpolation are performed to reduce block effects and errors from over-fitting. Simulation experiments show that our proposed CS based WZ codec associated with MAAR based SI generation achieves better results compared to other SI extrapolation methods.