A. Avudainayagam

Bio: A. Avudainayagam is an academic researcher. The author has contributed to research in topics: Turbo code & Encoder. The author has an hindex of 1, co-authored 1 publications receiving 18 citations.

Hyper-Trellis Decoding of Pixel-Domain Wyner–Ziv Video Coding

Abstract: In this paper, we present a new decoding algorithm for the Wyner-Ziv (WZ) video coding scheme based on turbo codes. In this scheme, a video frame is encoded using a turbo code, and only a subset of the parity bits are sent to the decoder. At the decoder, the temporal correlation of the video sequence is exploited by using the previous frame as noisy side information (SI) for the current frame. However, there is a mismatch between the SI, which is available as pixel values, and the binary code bits. Previous implementations of the decoder use suboptimal approaches that convert pixel values to soft information for code bits. We present a new decoding algorithm for this application based on decoding on a hyper-trellis, in which multiple states of the original code trellis are combined. We show that this approach significantly improves performance without changing the complexity of the decoder. We also introduce a new technique for the WZ decoder to exploit the spatial correlation within a frame without requiring transform-domain encoding at the encoder, thereby reducing its complexity. Simulation results for fixed-rate transmission show a 9-10-dB improvement in the peak signal-to-noise ratio when compared to a WZ video codec that does bitwise decoding and utilizes only the temporal correlation.

Correlation Noise Modeling for Efficient Pixel and Transform Domain Wyner–Ziv Video Coding

Abstract: In recent years, practical Wyner-Ziv (WZ) video coding solutions have been proposed with promising results. Most of the solutions available in the literature model the correlation noise (CN) between the original frame and its estimation made at the decoder, which is the so-called side information (SI), by a given distribution whose relevant parameters are estimated using an offline process, assuming that the SI is available at the encoder or the originals are available at the decoder. The major goal of this paper is to propose a more realistic WZ video coding approach by performing online estimation of the CN model parameters at the decoder, for pixel and transform domain WZ video codecs. In this context, several new techniques are proposed based on metrics which explore the temporal correlation between frames with different levels of granularity. For pixel-domain WZ (PDWZ) video coding, three levels of granularity are proposed: frame, block, and pixel levels. For transform-domain WZ (TDWZ) video coding, DCT bands and coefficients are the two granularity levels proposed. The higher the estimation granularity is, the better the rate-distortion performance is since the deeper the adaptation of the decoding process is to the video statistical characteristics, which means that the pixel and coefficient levels are the best performing for PDWZ and TDWZ solutions, respectively.

Efficient and Low-Complexity Surveillance Video Compression Using Backward-Channel Aware Wyner-Ziv Video Coding

Abstract: Video surveillance has been widely used in recent years to enhance public safety and privacy protection. A video surveillance system that deals with content analysis and activity monitoring needs efficient transmission and storage of the surveillance video data. Video compression techniques can be used to achieve this goal by reducing the size of the video with no or small quality loss. State-of-the-art video compression methods such as H.264/AVC often lead to high computational complexity at the encoder, which is generally implemented in a video camera in a surveillance system. This can significantly increase the cost of a surveillance system, especially when a mass deployment of end cameras is needed. In this paper, we discuss the specific considerations for surveillance video compression. We present a surveillance video compression system with low-complexity encoder based on Wyner-Ziv coding principles to address the tradeoff between computational complexity and coding efficiency. In addition, we propose a backward-channel aware Wyner-Ziv (BCAWZ) video coding approach to improve the coding efficiency while maintaining low complexity at the encoder. The experimental results show that for surveillance video contents, BCAWZ can achieve significantly higher coding efficiency than H.264/AVC intra coding as well as existing Wyner-Ziv video coding methods and is close to H.264/AVC inter coding, while maintaining similar coding complexity with intra coding. This shows that the low motion characteristics of many surveillance video contents and the low-complexity encoding requirement make our scheme a particularly suitable candidate for surveillance video compression. We further propose an error resilience scheme for BCAWZ to address the concern of reliable transmission in the backward-channel, which is essential to the quality of video data for real-time and reliable object detection and event analysis.

Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures

Abstract: Distributed video coding (DVC) is a relatively new video coding architecture originated from two fundamental theorems namely, Slepian–Wolf and Wyner–Ziv. Recent research developments have made DVC attractive for applications in the emerging domain of wireless video sensor networks (WVSNs). This paper reviews the state-of-the-art DVC architectures with a focus on understanding their opportunities and gaps in addressing the operational requirements and application needs of WVSNs.

Wyner-Ziv video coding with side matching for improved side information

Abstract: To make an encoder extremely simple by eliminating motion prediction/compensation from encoder, source coding with side information has been investigated based on the Wyner-Ziv theorem as the basic coding principle. However, the frame interpolation at decoder which is essential for redundancy elimination makes erroneous side information when the basic assumption of linear motion between frames is not satisfied. In this paper, we propose a new Wyner-Ziv video coding scheme featuring side matching in the frame interpolation to improve the side information. In the proposed scheme, Wyner-Ziv decoder compensates wrong blocks by side information using side matching and bi-directional searching. The noise reduction in side information allows the proposed algorithm to achieve coding improvements not only in bitrate but also in PSNR. Results of our experiments show improvement of PSNR up to 0.4dB.

Distributed image coding in wireless multimedia sensor networks: A survey

Abstract: There are a large number of video data have to be processed and transmitted in resource-constrained wireless multimedia sensor networks (WMSN). One possible way of achieving maximum utilization of those resources is to apply an adaptive image coding scheme, which must consider the trade-off between energy consumption and image quality. The the major research challenges and objectives of image coding for WMSN are discussed. Distributed image coding schemes especially designed for WMSN and some theoretical explorations are investigated and classified, including Wyner-Ziv coding and collaborative coding.