Channel Decoding Process Research Articles

Low Computational Coding-Efficient Distributed Video Coding: Adding a Decision Mode to Limit Channel Coding Load

Distributed video coding (DVC) is based on distributed source coding (DSC) concepts in which video statistics are used partially or completely at the decoder rather than the encoder. The rate-distortion (RD) performance of distributed video codecs substantially lags the conventional predictive video coding. Several techniques and methods are employed in DVC to overcome this performance gap and achieve high coding efficiency while maintaining low encoder computational complexity. However, it is still challenging to achieve coding efficiency and limit the computational complexity of the encoding and decoding process. The deployment of distributed residual video coding (DRVC) improves coding efficiency, but significant enhancements are still required to reduce these gaps. This paper proposes the QUAntized Transform ResIdual Decision (QUATRID) scheme that improves the coding efficiency by deploying the Quantized Transform Decision Mode (QUAM) at the encoder. The proposed QUATRID scheme's main contribution is a design and integration of a novel QUAM method into DRVC that effectively skips the zero quantized transform (QT) blocks, thus limiting the number of input bit planes to be channel encoded and consequently reducing both the channel encoding and decoding computational complexity. Moreover, an online correlation noise model (CNM) is specifically designed for the QUATRID scheme and implemented at its decoder. This online CNM improves the channel decoding process and contributes to the bit rate reduction. Finally, a methodology for the reconstruction of the residual frame (R^) is developed that utilizes the decision mode information passed by the encoder, decoded quantized bin, and transformed estimated residual frame. The Bjøntegaard delta analysis of experimental results shows that the QUATRID achieves better performance over the DISCOVER by attaining the PSNR between 0.06 dB and 0.32 dB and coding efficiency, which varies from 5.4 to 10.48 percent. In addition to this, results determine that for all types of motion videos, the proposed QUATRID scheme outperforms the DISCOVER in terms of reducing the number of input bit-planes to be channel encoded and the entire encoder's computational complexity. The number of bit plane reduction exceeds 97%, while the entire Wyner-Ziv encoder and channel coding computational complexity reduce more than nine-fold and 34-fold, respectively.

Utilization of multi-dimensional source correlation in multi-dimensional single parity check codes

This paper proposes a joint source-channel coding (JSCC) technique that well utilizes multi-dimensional (MD) source correlation using MD single parity check codes (MD-SPCCs). The source is assumed to be described by the coupling of multiple first-order binary Markov processes. The knowledge about the source correlation is utilized in the channel decoding process where each component decoder utilizes a single dimension correlation of the MD source. To enhance performance and reduce the error floor, a rate-1 recursive systematic convolutional code is serially concatenated to the MD-SPCC via a random interleaver. Two decoding techniques are proposed for each component decoder, and the selection of the decoding technique depends on the strength of the source correlation, which may further enhance the performance of the proposed JSCC technique. Simulation results reveal that a significant performance gain can be achieved by exploiting the MD source correlation with the proposed JSCC technique compared with the case in which the source correlation is not utilized; more significant gains can be achieved with stronger source correlation, and with a larger dimensionality source correlation as well.

Protocol-Assisted Channel Decoding

Channel decoding makes use of redundancy in the coded bits. However, any redundancy in the information bitstream can also improve the decoding process. This paper shows that a careful examination of communication standards (including the headers added by the network layers) exhibits some fields which can be considered as redundant, either based on already received packets, or on the standard. The efficient use of this knowledge in the channel decoding process is denoted as protocol-assisted channel decoding. Assuming perfect synchronization and available channel state information, the proposed method applied on 802.11a PHY and MAC layers provides a substantial link budget improvement without modifying the standard, while the introduction of an additional interleaver provides additional bit error rate improvements.

적응적 탐색 영역을 이용한 보조 정보 생성의 고속화 방법

분산 비디오 압축(DVC, Distributed Video Coding) 기술은 부호화기의 움직임 추정과 같은 복잡한 과정을 복호화기로 이동시킴으로써 경량화 비디오 부호화를 가능하게 하는 새로운 방법으로 주목 받고 있다. 한편, DVC 복호화기에서는 움직임 추정과 보상 과정뿐만 아니라 채널 복호 과정도 수행해야 하기 때문에 복호화기의 복잡도는 크게 증가하게 된다. 이에 복호화기 복잡도의 가장 많은 비중을 차지하는 채널 복호 과정을 고속화하기 위한 다양한 방법이 제안되고 있다. 하지만 다양한 고속화 방법에 의해 채널 복호 과정이 고속화될수록 채널 복호화 이외의 과정들에 대한 복잡도가 부각되는데, 일례로 DVC 복호화기에서 낮은 비율을 차지하던 보조 정보생성 과정의 복잡도가 상대적으로 증가된다. 따라서 본 논문에서는 보조 정보 생성 과정에 적응적 탐색 영역 방법을 적용하여 DVC 복호 과정을 고속화할 수 있는 알고리즘을 제안한다. 제안된 적응적 탐색 영역을 이용하는 방법을 적용할 경우 고정된 탐색 영역을 적용한 종래의 방법에 비해 평균적으로 보조 정보 생성 시간의 63% 정도가 절감 가능하며, 저하되는 율 왜곡 성능은 약 0.17%(BDBR) 정도로 상당히 낮다. In Distributed Video Coding(DVC), a low complexity encoder can be realized by shifting complex processes of encoder such as motion estimation to decoder. Since not only motion estimation/compensation processes but also channel decoding process needs to be performed at DVC decoder, the complexity of a decoder is significantly increased in consequence. Therefore, various fast channel decoding methods are proposed for the most computationally complex part, which is the channel decoding process in DVC decoding. As the channel decoding process becomes faster using various methods, however, the complexity of the other processes are relatively highlighted. For instance, the complexity of side information generation process in the DVC decoder is relatively increased. In this paper, therefore, a fast method for the DVC decoding is proposed by using adaptive search range method in side information generation process. Experimental results show that the proposed method achieves time saving of about 63% in side information generation process, while its rate distortion performance is degraded only by about 0.17% in BDBR.

Metadata-based image watermarking for copyright protection

In this paper, we propose a practical application for copyright protection of images with watermarking. The EXIF metadata of images and error-control codes are integrated into our algorithm and corresponding applications. Application for robust watermarking is one of the major branches in digital rights management (DRM) systems and digital forensics. Here, we focus on the copyright protection for images taken by ordinary cameras. By use of robust watermarking, it generally alters selected coefficients of the contents to accomplish the embedding process. Should the received image be in question, the watermark embedded beforehand can be extracted to indicate the copyright owner of such an image. We consider not only the image contents itself, but we also employ the EXIF metadata, which serves as the role of watermark, to be integrated into our scheme to make copyright protection possible. Moreover, for enhancing the performance for copyright protection, channel coding is employed and better protection capability can be expected. Taking the manufacturer, camera model, date and time stamp, and other important information in the EXIF metadata into account, conventional watermarking techniques can be applied to ordinary pictures taken by ourselves, and watermarked images with good quality can be produced. Even when the marked image has been intentionally modified, the original EXIF with selected information can mostly be recovered from the channel decoding process. Simulation results present the effectiveness of such an implementation.

공간적 유사성과 심볼단위 오류정정 채널 코드를 이용한 경량화 비디오 부호화 방법

기존의 부호화 기술은 부호화기의 복잡도가 복호화기에 비해 매우 높은 구조로 이루어져 있다. 하지만 최근에 부호화기 복잡도의 대부분을 차지했던 움직임 예측/보상과정을 없애는 경량화 부호화 구조에 대한 연구가 중요해졌다. Wyner-Ziv 부호화 기술은 이의 대표적인 기술로서 부호화기는 단순히 현재 프레임에 대한 패리티 정보만을 생성하며 프레임 간 유사성을 이용하는 어떠한 처리절차도 행하지 않기 때문에 종래의 기술에 비해 매우 간단한 구조를 갖는다. 하지만 Wyner-Ziv 부호화 구조에서는 잡음이 많은 보조영상을 복호화에 이용 할 경우 채널 코드의 복호화 오류가 발생한다. 이러한 복호화 오류는 특히 영상 간 유사성이 적어 보조정보를 잘 만들 수 없는 경우 더 많이 발생하며 복원된 영상에 마치 Salt & Pepper와 같은 형태의 잡음으로 나타난다. 이러한 잡음은 비록 그 발생빈도가 적더라도 복원된 영상의 주관적인 화질을 상당히 떨어뜨리는 요소로 작용하므로 이전에는 공간적 유사성을 이용하여 이러한 오류를 정정하는 선택적 미디언 필터를 사용한 경량화 부호화 방법을 제안하였었다. 하지만 이전 방법에서는 텍스처가 복잡한 영상의 경우, 필터적용에 따른 텍스처의 손실이 오류정정으로 얻는 이득보다 더 큰 경우가 발생하는 문제점이 있었다. 따라서 본 논문에서는 선택적 미디언 필터에 복원영상과 보조정보 내 잡음에 관한 정보를 제공함으로써 필터링에 따른 텍스처의 손실을 최소화하는 향상된 경량화 부호화 방법을 제안한다. 실험결과는 이전 방법에 비해 최대 0.84dB에 이르는 성능향상을 보였다. In conventional video coding, encoder complexity is much higher than that of decoder. However, investigations for lightweight encoder to eliminate motion prediction/compensation claiming most complexity in encoder have recently become an important issue. The Wyner-Ziv coding is one of the representative schemes for the problem and, in this scheme, since encoder generates only parity bits of a current frame without performing any type of processes extracting correlation information between frames, it has an extremely simple structure compared to conventional coding techniques. However, in Wyner-Ziv coding, channel decoding errors occur when noisy side information is used in channel decoding process. These channel decoding errors appear more frequently, especially, when there is not enough correlation between frames to generate accurate side information and, as a result, those errors look like Salt & Pepper type noise in the reconstructed frame. Since this noise severely deteriorates subjective video quality even though such noise rarely occurs, previously we proposed a computationally extremely light encoding method based on selective median filter that corrects such noise using spatial correlation of a frame. However, in the previous method, there is a problem that loss of texture from filtering may exceed gain from error correction by the filter for video sequences having complex torture. Therefore, in this paper, we propose an improved lightweight encoding method that minimizes loss of texture detail from filtering by allowing information of texture and that of noise in side information to be utilized by the selective median filter. Our experiments have verified average PSNR gain of up to 0.84dB compared to the previous method.