• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2851-2865
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• 2014

To improve the rate-distortion performance of distributed video compressive sensing (DVCS), the adaptive sparse basis and nonlocal similarity of video are proposed to jointly reconstruct the video signal in this paper. Due to the lack of motion information between frames and the appearance of some noises in the reference frames, the sparse dictionary, which is constructed using the examples directly extracted from the reference frames, has already not better obtained the sparse representation of the interpolated block. This paper proposes a method to construct the sparse dictionary. Firstly, the example-based data matrix is constructed by using the motion information between frames, and then the principle components analysis (PCA) is used to compute some significant principle components of data matrix. Finally, the sparse dictionary is constructed by these significant principle components. The merit of the proposed sparse dictionary is that it can not only adaptively change in terms of the spatial-temporal characteristics, but also has ability to suppress noises. Besides, considering that the sparse priors cannot preserve the edges and textures of video frames well, the nonlocal similarity regularization term has also been introduced into reconstruction model. Experimental results show that the proposed algorithm can improve the objective and subjective quality of video frame, and achieve the better rate-distortion performance of DVCS system at the cost of a certain computational complexity.

• Journal of Broadcast Engineering
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• v.19 no.2
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• pp.257-267
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• 2014

Distributed compressive video sensing (DCVS) is a low cost sampling paradigm for video coding based on the compressive sensing and the distributed video coding. In this paper, we propose using a skip-mode coding in DCVS under the assumption that in case of high temporal correlation, temporal interpolation can guarantee sufficiently good quality of nonkey frame, therefore no need to transmit measurement data in such a nonkey frame. Furthermore, we extend it to use a hierarchical structure for better temporal interpolation. Simulation results show that the proposed skip-mode coding can save the average subrate of whole video sequence while the PSNR is reduced only slightly. In addition, by using the proposed scheme, the computational complexity is also highly decreased at decoder on average by 43.75% for video sequences that have strong temporal correlation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5481-5495
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• 2018

Single pixel imaging technology has developed for years, however the video acquisition on the single pixel camera is not a well-studied problem in computer vision. This work proposes a new scheme for single pixel camera to acquire video data and a new regularization for robust signal recovery algorithm. The method establishes a single pixel video compressive sensing scheme to reconstruct the video clips in spatial domain by recovering the difference of the consecutive frames. Different from traditional data acquisition method works in transform domain, the proposed scheme reconstructs the video frames directly in spatial domain. At the same time, a new regularization called spatial cluster is introduced to improve the performance of signal reconstruction. The regularization derives from the observation that the nonzero coefficients often tend to be clustered in the difference of the consecutive video frames. We implement an experiment platform to illustrate the effectiveness of the proposed algorithm. Numerous experiments show the well performance of video acquisition and frame reconstruction on single pixel camera.

• 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 Satellite, Information and Communications
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• v.9 no.2
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• pp.63-68
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• 2014

This paper proposed a novel compressed sensing (CS) technique for an efficient video transmission of multi-copter. The proposed scheme is focused on reduction of the amount of data based on CS technology. First, we describe basic principle of Spectrum sensing. And then we compare AMP(Approximate Message Passing) with CoSaMP(Compressive Sampling Matched Pursuit) through mathematical analysis and simulation results. They are evaluated in terms of calculation time and complexity, then the promising algorithm is suggestd for multicopter operation. The result of experiment in this paper shows that AMP algorithm is more efficient than CoSaMP algorithm when it comes to calculation time and image error probability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.321-340
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• 2016

The Compressive Video Sensing (CVS) is a useful technology for wireless systems requiring simple encoders but handling more complex decoders, and its rate-distortion performance is highly affected by the quantization of measurements and reconstruction of video frame, which motivates us to presents the Space-Time Quantization (ST-Q) and Motion-Aligned Reconstruction (MA-R) in this paper to both improve the performance of CVS system. The ST-Q removes the space-time redundancy in the measurement vector to reduce the amount of bits required to encode the video frame, and it also guarantees a low quantization error due to the fact that the high frequency of small values close to zero in the predictive residuals limits the intensity of quantizing noise. The MA-R constructs the Multi-Hypothesis (MH) matrix by selecting the temporal neighbors along the motion trajectory of current to-be-reconstructed block to improve the accuracy of prediction, and besides it reduces the computational complexity of motion estimation by the extraction of static area and 3-D Recursive Search (3DRS). Extensive experiments validate that the significant improvements is achieved by ST-Q in the rate-distortion as compared with the existing quantization methods, and the MA-R improves both the objective and the subjective quality of the reconstructed video frame. Combined with ST-Q and MA-R, the CVS system obtains a significant rate-distortion performance gain when compared with the existing CS-based video codecs.

• 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.

• 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.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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4160-4176
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• 2015

Data compression like image and video compression has come a long way since the introduction of Compressive Sensing (CS) which compresses sparse signals such as images, videos etc. to very few samples i.e. M < N measurements. At the receiver end, a robust and efficient recovery algorithm estimates the original image or video. Many prominent algorithms solve least squares problem (LSP) iteratively in order to reconstruct the signal hence consuming more processing time. In this paper non-iterative threshold based recovery algorithm (NITRA) is proposed for the recovery of images and videos without solving LSP, claiming reduced complexity and better reconstruction quality. The elapsed time for images and videos using NITRA is in ㎲ range which is 100 times less than other existing algorithms. The peak signal to noise ratio (PSNR) is above 30 dB, structural similarity (SSIM) and structural content (SC) are of 99%.