• Journal of Broadcast Engineering
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• v.13 no.6
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• pp.892-904
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• 2008

As a video encoding in resource constrained environments such as sensor networks has become an important issue, DVC(Distributed Video Coding) has been intensively investigated as a solution for light weighted video encoding problem. Known as one of the representative schemes of DVC, the Wyner-Ziv coding generates side information of current frame only at decoder, using correlation among frames, and reconstructs video through noise elimination on the side information using channel code. Accordingly, the better quality of side information brings less channel noise, thus attains better coding performance of the Wyner-Ziv coder. However, since it is hard for decoder to generate an accurate side information without any information of original frame, a method to successively improve side information using successively decoded original frame, based on decoding reliability, was previously developed. However, to improve side information from decoding results, not only an error rate of the decoding result as a reliability, but also the amount of reliable information from the decoding result is important. Therefore, we propose TDWZ(Transform-domain Wyner-Ziv coding) with successively improving side information based on decoding reliability considering not only an error rate but also the amount of reliable information of the decoding results. Our experiment shows the proposed method gains average PSNR up to 1.7 dB over the previous TDWZ, that is without successive side information improvement.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.136-137
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• 2010

본 논문에서는 고속, 저전력 비디오 부호화에 적합한 변환영역 Wyner-Ziv 분산비디오부호화기를 더욱 고속화하기 위한 병렬처리 방법을 제안한다. 기존에는 변환영역 Wyner-Ziv 분산비디오부호화를 위해 양자화 정보를 비트플레인단위로 분해후 이를 순차적으로 LDPCA 부호화하여 전체 부호화기 연산량에서 LDPCA의 복잡도가 약 54% 정도 차지하였고, 이는 고비트율로 부호화 할수록 더욱 증가하였다. 제안방법은 이를 개선하기 위해 여러 개의 비트플레인을 하나의 심벌 (symbol)로 묶어서 LDPCA 부호화를 수행하여 한 번의 연산으로 여러 개의 데이터를 동시에 처리할 수 있게 한다. 일종의 단일 명령 복수 데이터 처리 (SIMD, Single instruction, multiple data)에 의한 고속화 방법이다. 이를 통해 제안방법은 기존의 순차적 처리 방법에 비해 저비트율에서는 8배, 고비트율에서는 55배까지 LDPCA의 부호화 속도를 향상시켰다. 결과적으로 전체 부호화에서 LDPCA의 상대적인 복잡도 비율은 4%정도로 낮아지게 되었으며 Wyner-Ziv 영상의 부호화 속도도 약 1.5 ~ 2배까지 향상되었다. 제안방법은 LDPCA를 사용하는 다른 Wyner-Ziv 분산비디오부호화 구조에도 적용 가능할 것으로 기대한다.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.2
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• pp.129-142
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• 2016

In Wyner-Ziv coding, video signals are reconstructed by correcting side information generated by block-based motion estimation/compensation at the decoder. The correction is not always accurate due to the limited number of parity bits and early stopping of low-density parity check accumulate (LDPCA) decoding in distributed video coding, or due to the limited number of measurements in distributed compressive video sensing. The blocking artifacts caused by block-based processing are usually conspicuous in smooth areas and degrade the perceptual quality of the reconstructed video. Conventional deblocking filters try to remove the artifacts by treating both sides of the block boundary equally; however, coding errors generated by block-based processing are not necessarily the same on both sides of the block boundaries. Such a block-wise difference is exploited in this paper to improve deblocking for Wyner-Ziv frameworks by designing a filter where the deblocking strength at each block can be non-identical, depending on the reliability of the reconstructed pixels. Test results show that the proposed filter not only improves subjective quality by reducing the coding artifacts considerably, but also gains rate distortion performance.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.381-384
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• 2009

In the Wyner-Ziv coding, compression performance highly depends on the quality of the side information since better quality of side information brings less channel noise and less parity bit. However, as decoder generates side information without any knowledge of the current Wyner-Ziv frame, it doesn't have optimal criterion to decide which block is more advantageous to generate better side information. Hence, in general, fixed block size motion estimation (ME) is performed in generating side information. By the fixed block size ME, the best coding performance cannot be attained since some blocks are better to be motion estimated in different block sizes. Therefore if there is a way to find appropriate ME block of each block, the quality of the side information might be improved. In this paper, we investigate the effects of variable block sizes of ME in generating side information.

• Journal of Broadcast Engineering
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• v.16 no.3
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• pp.510-519
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• 2011

Intra mode decision is a useful coding tool in Distributed Video Coding (DVC) for improving DVC coding efficiency for video sequences having fast motion. A major limitation associated with the existing intra mode decision methods, however, is that its efficiency highly depends on user-specified thresholds or modeling parameters. This paper proposes an entropy-based method to address this problem. The probabilities of intra and Wyner?Ziv (WZ) modes are determined firstly by examining correlation of pixels in spatial and temporal directions. Based on these probabilities, entropy of the intra and the WZ modes are computed. A comparison based on the entropy values decides a coding mode between intra coding and WZ coding without relying on any user-specified thresholds or modeling parameters. Experimental results show its superior rate-distortion performance of improvements of PSNR up to 2 dB against a conventional Wyner?Ziv coding without intra mode decision. Furthermore, since the proposed method does not require any thresholds or modeling parameters from users, it is very attractive for real life applications.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.58-66
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• 2009

Recently the emerging demands of the light-video encoder promotes lots of research efforts on DVC (Distributed Video Coding). As an appropriate video compression method, DVC has been studied, and Wyner-Ziv (WZ) video compression is its one representative structure. The WZ encoder splits the image into two kinds of frames, one is key frame which is compressed by conventional intra coding, and the other is WZ frame which is encoded by WZ coding. The WZ decoder decodes the key frame first, and estimates the WZ frame using temporal correlation between key frames. Estimated WZ frame (Side Information) cannot be the same as the original WZ frame due to the absence of the WZ frame information at decoder. As a result, the difference between the estimated and original WZ frames are regarded as virtual channel noise. The WZ frame is reconstructed by removing noise in side information. Therefore precise noise estimation produces good performance gain in WZ video compression by improving error correcting capability by channel code. But noise cannot be estimated precisely at WZ decoder unless there is good WZ frame information, and generally it is estimated from the difference of corresponding key frames. Also the estimated noise is limited by comparing with frame level noise to reduce the uncertainty of the estimation method. However these methods cannot provide good noise estimation for every frame or each bit plane. In this paper, we propose a noise nodel selection method which chooses a better noise model for each bit plane after generating candidate noise models. Experimental result shows PSNR gain up to 0.8 dB.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.1
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• pp.11-21
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• 2008

In conventional video coding, the complexity of encoder is much higher than that of decoder. However, as more needs arises for extremely simple encoder in environments having constrained energy such as sensor network, much investigation has been carried out for eliminating motion prediction/compensation claiming most complexity and energy in encoder. The Wyner-Ziv coding, one of the representative schemes for the problem, reconstructs video at decoder by correcting noise on side information using channel coding technique such as turbo code. Since the encoder generates only parity bits without performing any type of processes extracting correlation information between frames, it has an extremely simple structure. However, turbo decoding errors occur in noisy side information. When there are high-motion or occlusion between frames, more turbo decoding errors appear in reconstructed frame and look like Salt & Pepper noise. This severely deteriorates subjective video quality even though such noise rarely occurs. In this paper, we propose a computationally extremely light encoder based on symbol-level Wyner-Ziv coding technique and a new corresponding decoder which, based on a decision whether a pixel has error or not, applies median filter selectively in order to minimize loss of texture detail from filtering. The proposed method claims extremely low encoder complexity and shows improvements both in subjective quality and PSNR. Our experiments have verified average PSNR gain of up to 0.8dB.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2008.11a
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• pp.81-84
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• 2008

최근 센서네트워크와 같은 에너지 제한 환경을 위한 경량화 부호화 기술의 필요성이 대두됨에 따라 분산 소스 부호화 기술(Distributed Source Coding)의 응용기술로 비디오 부호화 복잡도의 대부분을 차지하는 움직임 예측/보상과정을 부호화기가 아닌 복호화기에서 수행하는 분산 비디오 부호화 기술(Distributed Video Coding)에 대한 연구가 활발히 이루어져 왔다. 이에 가장 대표적인 기술인 Wyner-Ziv 코딩 기술은 채널 코드를 이용하여 원본 프레임과 이에 대한 복호화기의 예측영상인 보조정보 사이의 잡음을 제거하여 영상을 복원한다. 일반적으로 보조정보는 원본영상에 유사한 키 프레임간의 프레임 보간을 통하여 생성되며 채널 코드는 Shannon limit에 근접한 성능을 보이는 Turbo 코드나 LDPC 코드가 사용된다. 이와 같은 채널 코드의 복호화는 채널 잡음 모델에 기반하여 수행되어지며 Wyner-Ziv 코딩 기술에서는 이 채널 잡음 모델을 '상관 잡음 모델' (Correlation Noise Modeling)이라 하고 일반적으로 Laplacian이나 Gaussian으로 모델화 한다. 하지만 복호화기에는 원본 영상에 대한 정보가 없기 때문에 정확한 상관 잡음 모델을 알 수 없으며 잡음 모델에 대한 예측의 부정확성은 잡음 제거를 위한 패리티 비트의 증가를 야기해 부호화 기술의 압축 성능 저하를 가져온다. 이에 본 논문은 원본 프레임과 보조정보 사이의 잡음을 정확하게 예측하여 잡음을 정정할 수 있는 향상된 상관 잡음 모델을 제안한다. 제안 방법은 잘못된 잡음 예측에 의해 Laplacian 계수가 너무 커지는 것을 방지하면서 영상내의 잡음의 유무에 별다른 영향을 받지 않는 새로운 문턱값을 사용한다. 다양한 영상에 대한 제안 방법의 실험 결과는 평균적으로 약 0.35dB에 해당하는 율-왜곡 성능 향상을 보여주었다.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.160-172
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• 2014

Although Wyner-Ziv (WZ) video coding proves useful for applications employing encoders having restricted computing resources, the WZ decoder has a problem of excessive decoding complexity. It is mainly due to its iterative LDPC channel decoding process which repeatedly requests incremental parity data after iterative channel decoding of parity data received at each request. In order to solve the complexity problem, we divide bit planes into two groups and estimate the minimum required number of parity requests separately for the two groups of bit planes using bit plane correlation. The WZ decoder executes the iterative decoding process only after receiving parity data corresponding to the estimated minimum number of parity requests. The proposed method saves about 71% of the computing time in the LDPC decoding process.

• 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.