Mortuza Ali

A Parametric Approach to List Decoding of Reed-Solomon Codes Using Interpolation

In this paper, we present a minimal list decoding algorithm for Reed-Solomon (RS) codes. Minimal list decoding for a code C refers to list decoding with radius L, where L is the minimum of the distances between the received word r and any codeword in C. We consider the problem of determining the value of L as well as determining all the codewords at distance L. Our approach involves a parametrization of interpolating polynomials of a minimal Gröbner basis G . We present two efficient ways to compute G. We also show that so-called re-encoding can be used to further reduce the complexity. We then demonstrate how our parametric approach can be solved by a computationally feasible rational curve fitting solution from a recent paper by Wu. Besides, we present an algorithm to compute the minimum multiplicity as well as the optimal values of the parameters associated with this multiplicity, which results in overall savings in both memory and computation.

Source coding with side information using list decoding

Existing literature on source coding with side information (SCSI) uses channel codes like LDPC codes and turbo codes and assumes classical unique decoding. In this paper, in contrast to classical decoding, we have taken the list decoding approach and show that the theoretical limit of SCSI can then be achieved. We argue that, as opposed to channel coding, the correct sequence from the list produced by the list decoder can effectively be recovered in case of SCSI with a few CRC bits. The CRC bits, which allow the decoder to identify the correct sequence, incur negligible overhead for large block length. More importantly, these CRC bits are not subject to noise since we are dealing with a virtual noisy channel rather than a real noisy channel. Finally, we present a guideline for designing constructive SCSI schemes using Reed Solomon code, BCH code, and Reed-Muller code, which are the known list-decodable codes.

Efficient Coding of Depth Map by Exploiting Temporal Correlation

With the growing demands for 3D and multi-view video content, efficient depth data coding becomes a vital issue in image and video coding area. In this paper, we propose a simple depth coding scheme using multiple prediction modes exploiting temporal correlation of depth map. Current depth coding techniques mostly depend on intra-coding mode that cannot get the advantage of temporal redundancy in the depth maps and higher spatial redundancy in inter-predicted depth residuals. Depth maps are characterized by smooth regions with sharp edges that play an important role in the view synthesis process. As depth maps are more sensitive to coding errors, use of transformation or approximation of edges by explicit edge modelling has impact on view synthesis quality. Moreover, lossy compression of depth map brings additional geometrical distortion to synthetic view. In this paper, we have demonstrated that encoding inter-coded depth block residuals with quantization at pixel domain is more efficient than the intra-coding techniques relying on explicit edge preservation. On standard 3D video sequences, the proposed depth coding has achieved superior image quality of synthesized views against the new 3D-HEVC standard for depth map bit-rate 0.25 bpp or higher.

A Novel Video Coding Scheme using a Scene Adaptive Non-Parametric Background Model

Video coding techniques utilising background frames, provide better rate distortion performance by exploiting coding efficiency in uncovered background areas compared to the latest video coding standard. Parametric approaches such as the mixture of Gaussian (MoG) based background modeling has been widely used however they require prior knowledge about the test videos for parameter estimation. Recently introduced non-parametric (NP) based background modeling techniques successfully improved video coding performance through a HEVC integrated coding scheme. The inherent nature of the NP technique naturally exhibits superior performance in dynamic background scenarios compared to the MoG based technique without a priori knowledge of video data distribution. Although NP based coding schemes showed promising coding performances, they suffer from a number of key challenges - (a) determination of the optimal subset of training frames for generating a suitable background that can be used as a reference frame during coding, (b) incorporating dynamic changes in the background effectively after the initial background frame is generated, (c) managing frequent scene change leading to performance degradation, and (d) optimizing coding quality ratio between an I-frame and other frames under bit rate constraints. In this study we develop a new scene adaptive coding scheme using the NP based technique, capable of solving the current challenges by incorporating a new continuously updating background generation process. Extensive experimental results are also provided to validate the effectiveness of the new scheme.

An efficient cooperative lane-changing algorithm for sensor- and communication-enabled automated vehicles

A key goal in transportation system is to attain efficient road traffic through minimization of trip time, fuel consumption and pollutant-emission without compromising safety. In dense traffic lane-changes and merging are often key ingredients to cause safety hazards, traffic breakdowns and travel delays. In this paper, we propose an efficient cooperative lane-changing algorithm CLA for sensor- and communication-enabled automated vehicles to reduce the lane-changing bottlenecks. For discretionary lane-changing, we consider the advantages of the subject vehicle, the follower in the current lane and k (an integer) lag vehicles in the target lane to maximize speed gains. Our algorithm simultaneously minimizes the impact of lane-change on traffic flow and the overall trip time, fuel-consumption and pollutant-emission. For mandatory lane-changing CLA dissociates the decision-making point from the actual mandatory lane-changing point and computes a suitable lane-changing slot in order to minimize lane-changing (merging) time. Our algorithm outperforms the potential cooperative lane-changing algorithm MOBIL proposed by Kesting et al. [1] in terms of merging time and rate, waiting time, fuel consumption, average velocity and flow (especially at the point in front of the merging point) at the cost of slightly increased average trip time for the mainroad vehicles compared to MOBIL. We also highlight important directions for further research.

Adaptive weighted non-parametric background model for efficient video coding

Dynamic background frame based video coding using mixture of Gaussian (MoG) based background modelling has achieved better rate distortion performance compared to the H.264 standard. However, they suffer from high computation time, low coding efficiency for dynamic videos, and prior knowledge requirement of video content. In this paper, we introduce the application of the non-parametric (NP) background modelling approach for video coding domain. We present a novel background modelling technique, called weighted non-parametric (WNP) which balances the historical trend and the recent value of the pixel intensities adaptively based on the content and characteristics of any particular video. WNP is successfully embedded into the latest HEVC video coding standard for better rate-distortion performance. Moreover, a novel scene adaptive non-parametric (SANP) technique is also developed to handle video sequences with high dynamic background. Being non-parametric, the proposed techniques naturally exhibit superior performance in dynamic background modelling without a priori knowledge of video data distribution.

A novel depth motion vector coding exploiting spatial and inter-component clustering tendency

Motion vectors of depth-maps in multiview and free-viewpoint videos exhibit strong spatial as well as inter-component clustering tendency. This paper presents a novel coding technique that first compresses the multidimensional bitmaps of macroblock mode and then encodes only the non-zero components of motion vectors. The bitmaps are partitioned into disjoint cuboids using binary tree based decomposition so that the 0s and 1s are either highly polarized or further sub-partitioning is unlikely to achieve any compression. Each cuboid is entropy-coded as a unit using binary arithmetic coding. This technique is capable of exploiting the spatial and inter-component correlations efficiently without the restriction of scanning the bitmap in any specific linear order as needed by run-length coding. As encoding of non-zero component values no longer requires denoting the zero value, further compression efficiency is achieved. Experimental results on standard multiview test video sequences have comprehensively demonstrated the superiority of the proposed technique, achieving overall coding gain against the state-of-the-art in the range [22%, 54%] and on average 38%.

Cuboid Coding of Depth Motion Vectors Using Binary Tree Based Decomposition

Motion vectors of depth-maps in multiview and free-viewpoint videos exhibit strong spatial as well as inter-component clustering tendency. This paper presents a novel motion vector coding technique that first compresses the multidimensional bitmaps of macro block mode information and then encodes only the non-zero components of motion vectors. The bitmaps are partitioned into disjoint cuboids using binary tree based decomposition so that the 0s and 1s are either highly polarized or further sub-partitioning is unlikely to achieve any compression. Each cuboid is entropy-coded as a unit using binary arithmetic coding. This technique is capable of exploiting the spatial and inter-component correlations efficiently without the restriction of scanning the bitmap in any specific linear order as needed by run-length coding. As encoding of non-zero component values no longer requires denoting the zero value, further compression efficiency is achieved. Experimental results on standard multiview test video sequences have comprehensively demonstrated the superiority of the proposed technique, achieving overall coding gain against the state-of-the-art in the range [17%,51%] and on average 31%.

Inherently edge-preserving depth-map coding without explicit edge detection and approximation

In emerging 3D video coding, depth has significant importance in view synthesis, scene analysis, and 3D object reconstruction. Depth images can be characterized by sharp edges and smooth large regions. Most of the existing depth coding techniques use intra-coding mode and try to preserve edges explicitly with approximated edge modelling. However, edges can be implicitly preserved as long as the transformation is avoided. In this paper, we have demonstrated that inherent edge preserving encoding of inter-coded block residuals, uniformly quantized at pixel domain using motion data from associated texture components, is more efficient than explicitly edge preserving intra-coding techniques. Experimental results show that the proposed technique have achieved superior image quality of synthesized views against the new 3D-HEVC standard. Lossless applications of the proposed technique has achieved on average 66% and 23% bit-rate savings against 3D-HEVC with negligible quantization and perceptually unnoticeable view synthesis, respectively.

Efficient contention resolution in MAC protocol for periodic data collection in WSNs

Due to the infrequent medium access in Wireless Sensor Networks (WSN), their MAC protocols are mostly based on CSMA. In this paper we present an efficient contention resolution scheme for CSMA based MAC protocols which is suitable for periodic data collection in WSNs. Taking into account that the number of nodes in a single cluster is fixed, this protocol uses successively decreasing contention window. It is characterized by non-overlapping contention window, that maintains a constant successful transmission rate. It significantly decreases data collection time by minimizing the time wastage due to collisions. At the same time, by using adaptive CW, it reduces the time wastage in empty slots. Experimental results demonstrate that in periodic data collection within a single hop cluster this scheme has performance superior to the recently proposed Synchronous Shared Contention Window (SSCW) based scheme in terms of time wastage and throughput.