15323037
Successive refinement for the Wyner-Ziv problem and layered code design
We examine successive refinement for the Wyner-Ziv problem described in a recent paper by Steinberg and Merhav, where the authors showed that if the side information for all stages is identical, then the jointly Gaussian source with squared error distortion measure is successively refinable. We first extend this result to the case where the difference between the source and the side information is Gaussian and independent of the side information. As a byproduct, we give an alternative proof that the Wyner-Ziv problem for these sources has no rate loss-a result that was recently shown by Pradhan et al. through invoking the duality between the Gaussian Wyner-Ziv problem and the Costa problem. We then perform layered Wyner-Ziv code design for this general type of source based on nested scalar quantization, bit-plane coding, and low-density parity check (LDPC) code-based Slepian-Wolf coding (source coding with side information). We show that density evolution can be used to analyze the Slepian-Wolf code performance, provided that certain symmetry conditions, which have been dubbed dual symmetry, are satisfied by the hypothetical channel between the source and the side information. We also show that the dual symmetry condition is indeed satisfied by the hypothetical channel in our Slepian-Wolf coding setup. This justifies the use of density evolution in our LDPC code-based Slepian-Wolf code design for Wyner-Ziv coding. For the jointly Gaussian source, our layered coder performs 1.29 to 3.45 dB from the Wyner-Ziv bound for rates ranging from 0.47 to 4.68 bits per sample. When the side information is Laplacian and the source equals the side information plus an independent Gaussian noise term, our layered coder performs 1.33 to 3.90 dB from the Wyner-Ziv bound for rates ranging from 0.48 to 4.64 bits per sample.
20227157
Trellis coded color quantization of images
We examine color quantization of images using trellis coded quantization (TCQ). Together with a simple dithering scheme, an 8-bit trellis coded color quantizer reproduces images that are visually indistinguishable from the 24-bit originals. The proposed algorithm can be viewed as a predictive trellis coded color quantization scheme. It is universal in the sense that no training or lookup table is needed. The complexity of TCQ is linear with respect to image size, making trellis coded color quantization suitable for interactive graphics and a window-based display environment.
15084916
Computing the channel capacity and rate-distortion function with two-sided state information
In this correspondence, we present iterative algorithms that numerically compute the capacity-power and rate-distortion functions for coding with two-sided state information. Numerical examples are provided to demonstrate efficiency of our algorithms.
18292356
On dualities in multiterminal coding problems
It has been shown recently that under certain conditions there exist dualities between different multiterminal (MT) source and channel coding problems. Following these results, we study lossless MT source coding and deterministic MT channel coding problems and point out different dualities between them. In particular, we show that there exists a functional duality between a Slepian-Wolf (SW) coding problem and a deterministic broadcast channel (DBC) coding problem and between a lossless multiple-description (MD) coding problem and a deterministic multiple-access channel (DMAC) coding problem. In analogy to the duality established between DBC and DMAC coding problems, we further propose a similar duality between SW and lossless MD coding problems; in this way, we form a closed "duality loop" of four MT coding problems, which imposes the existence of a single common rate point in the achievable rate regions of all four dual problems. We also consider duality in zero-error MT coding and shed light on practical code design with an example. Finally, extension to the case with only one lossless/deterministic component in the source/channel coding problem is provided.
15109463
Slepian-Wolf Coded Nested Lattice Quantization for Wyner-Ziv Coding: High-Rate Performance Analysis and Code Design
Nested lattice quantization provides a practical scheme for Wyner-Ziv coding. This paper examines the high-rate performance of nested lattice quantizers and gives the theoretical performance for general continuous sources. In the quadratic Gaussian case, as the rate increases, we observe an increasing gap between the performance of finite-dimensional nested lattice quantizers and the Wyner-Ziv distortion-rate function. We argue that this is because the boundary gain decreases as the rate of the nested lattice quantizers increases. To increase the boundary gain and ultimately boost the overall performance, a new practical Wyner-Ziv coding scheme called Slepian-Wolf coded nested lattice quantization (SWC-NQ) is proposed, where Slepian-Wolf coding is applied to the quantization indices of the source for the purpose of compression with side information at the decoder. Theoretical analysis shows that for the quadratic Gaussian case and at high rate, SWC-NQ performs the same as conventional entropy-coded lattice quantization with the side information available at both the encoder and the decoder. Furthermore, a nonlinear minimum mean-square error (MSE) estimator is introduced at the decoder, which is theoretically proven to degenerate to the linear minimum MSE estimator at high rate and experimentally shown to outperform the linear estimator at low rate. Practical designs of one- and two-dimensional nested lattice quantizers together with multilevel low-density parity-check (LDPC) codes for Slepian-Wolf coding give performance close to the theoretical limits of SWC-NQ
6799009
On packetization of embedded multimedia bitstreams
We study the problem of packetizing embedded multimedia bitstreams to improve the error resilience of source (compression) codes. This problem is important because of the increasing popularity of embedded compression methodology and its suitability for scalable streaming media over IP or/and mobile IP. We study various packetization schemes against packet erasure at both low and high bit rates. Maximizing packetization efficiency for embedded bitstreams is formulated as a discrete optimization problem and globally optimal packetization (OP) algorithms are proposed under different settings. Suboptimal packetization algorithms are also devised to reduce the complexity of the OP algorithms. In order to assess their effectiveness, the proposed packetization algorithms are used to packetize embedded image and video bitstreams with simulated packet loss. Experimental results show that our OP algorithms slightly outperforms suboptimal ones. In addition to confirming the superiority of the OP algorithms, these results also provide justification of heuristic packetization methods published in the literature.
15245491
Efficient Expected-Case Algorithms for Planar Point Location
Planar point location is among the most fundamental search problems in computational geometry. Although this problem has been heavily studied from the perspective of worst-case query time, there has been surprisingly little theoretical work on expected-case query time. 
 
We are given an n-vertex planar polygonal subdivision S satisfying some weak assumptions (satisfied, for example, by all convex subdivisions). 
 
We are to preprocess this into a data structure so that queries can be answered efficiently. We assume that the two coordinates of each query point are generated independently by a probability distribution also satisfying some weak assumptions (satisfied, for example, by the uniform distribution). 
 
In the decision tree model of computation, it is well-known from information theory that a lower bound on the expected number of comparisons is entropy(S). We provide two data structures, one of size O(n2) that can answer queries in 2 entropy(S) + O(1) expected number of comparisons, and another of size O(n) that can answer queries in (4 + O(1/√log n)) entropy(S)+O(1) expected number of comparisons. These structures can be built in O(n2) and O(n log n) time respectively. Our results are based on a recent result due to Arya and Fu, which bounds the entropy of overlaid subdivisions.
14292166
A self-adjusting quality of service control scheme
We propose and analyze a self-adjusting Quality of Service (QoS) control scheme with the goal of optimizing the system reward as a result of servicing different priority clients with varying workload, QoS and reward/penalty requirements. Our scheme is based on resource partitioning and designated "degrade QoS areas" such that system resources are partitioned into priority areas each of which is reserved specifically to serve only clients in a corresponding class with no QoS degradation, plus one "degraded QoS area" into which all clients can be admitted with QoS adjustment being applied only to the lowest priority clients. We show that the best partition is dictated by the workload and the reward/penalty characteristics of clients in difference priority classes. The analysis results can be used by a QoS manager to optimize the system total rewawrd dynamically in response to changing workloads at run time. We demonstrate the validity of our scheme by means of simulation and comparing the proposed QoS self-adjusting scheme with those that do not use resource partitioning or designated degraded QoS area.
76461
Software Architecture-Based Adaptation for Pervasive Systems
An important requirement for pervasive computing systems is the ability to adapt at runtime to handle varying resources, user mobility, changing user needs, and system faults. In this paper we describe an approach in which dynamic adaptation is supported by the use of software architectural models to monitor an application and guide dynamic changes to it. The use of externalized models permits one to make reconfiguration decisions based on a global perspective of the running system, apply analytic models to determine correct repair strategies, and gauge the effectiveness of repair through continuous system monitoring. We illustrate the application of this idea to pervasive computing systems, focusing on the need to adapt based on performance-related criteria and models.
359856
Curve reconstruction from noisy samples
We present an algorithm to reconstruct a collection of disjoint smooth closed curves from n noisy samples. Our noise model assumes that the samples are obtained by first drawing points on the curves according to a locally uniform distribution followed by a uniform perturbation of each point in the normal direction with a magnitude smaller than the minimum local feature size. The reconstruction is faithful with a probability that approaches 1 as n increases.We expect that our approach can lead to provable algorithms under less restrictive noise models and for handling non-smooth features.
1344352
Quality meshing for polyhedra with small angles
We present an algorithm to compute a Delaunay mesh conforming to a polyhedron possibly with small input angles. The radius-edge ratio ofmost output tetrahedra are bounded by a constant, except possibly those that are provably close to small angles. Further, the mesh is graded, that is, edge lengths are at least a constant fraction of the local feature sizes at the edge endpoints. Unlike a previous algorithm, this algorithm is simple to implement as it avoids computing local feature sizes and protective zones explicitly. Our experimental results confirm our claims and show that few skinny tetrahedra remain.