This comprehensive treatment of network information theory and its applications provides the first unified coverage of both classical and recent results. With an approach that balances the introduction of new models and new coding techniques, readers are guided through Shannon's point-to-point information theory, single-hop networks, multihop networks, and extensions to distributed computing, secrecy, wireless communication, and networking. Elementary mathematical tools and techniques are used throughout, requiring only basic knowledge of probability, whilst unified proofs of coding theorems are based on a few simple lemmas, making the text accessible to newcomers. Key topics covered include successive cancellation and superposition coding, MIMO wireless communication, network coding, and cooperative relaying. Also covered are feedback and interactive communication, capacity approximations and scaling laws, and asynchronous and random access channels. This book is ideal for use in the classroom, for self-study, and as a reference for researchers and engineers in industry and academia.

Network Information Theory

Information Theory and Reliable Communication

Sphere Packings, Lattices and Groups

Systems and methods for implementing array cameras configured to perform super- resolution processing to generate higher resolution super-resolved images using a plurality of captured images and lens stack arrays that can be utilized in array cameras are disclosed. Lens stack arrays in accordance with many embodiments of the invention include lens elements formed on substrates separated by spacers, where the lens elements, substrates and spacers are configured to form a plurality of optical channels, at least one aperture located within each optical channel, at least one spectral filter located within each optical channel, where each spectral filter is configured to pass a specific spectral band of light, and light blocking materials located within the lens stack array to optically isolate the optical channels.

Capturing and processing of images using monolithic camera array with heterogeneous imagers

Product design is a highly involved, often ill-defined, complex and iterative process, and the needs and specifications of the required artifact get more refined only as the design process moves toward its goal. An effective computer support tool that helps the designer make better-informed decisions requires efficient knowledge representation schemes. In today's world, there is a virtual explosion in the amount of raw data available to the designer, and knowledge representation is critical in order to sift through this data and make sense of it. In addition, the need to stay competitive has shrunk product development time through the use of simultaneous and collaborative design processes, which depend on effective transfer of knowledge between teams. Finally, the awareness that decisions made early in the design process have a higher impact in terms of energy, cost, and sustainability, has resulted in the need to project knowledge typically required in the later stages of design to the earlier stages. Research in design rationale systems, product families, systems engineering, and ontology engineering has sought to capture knowledge from earlier product design decisions, from the breakdown of product functions and associated physical features, and from customer requirements and feedback reports. VR (Virtual reality) systems and multidisciplinary modeling have enabled the simulation of scenarios in the manufacture, assembly, and use of the product. This has helped capture vital knowledge from these stages of the product life and use it in design validation and testing. While there have been considerable and significant developments in knowledge capture and representation in product design, it is useful to sometimes review our position in the area, study the evolution of research in product design, and from past and current trends, try and foresee future developments. The goal of this paper is thus to review both our understanding of the field and the support tools that exist for the purpose, and identify the trends and possible directions research can evolve in the future.

/pdf/the-evolution-challenges-and-future-of-knowledge-2l8tzvf3b5.pdf

The evolution, challenges, and future of knowledge representation in product design systems

A system that incorporates the subject disclosure may include, for example, partitioning the image into a group of blocks, calculating principle bilateral filtered image components for a first subset of the group of blocks where the principle bilateral filtered image components are not calculated for a second subset of the group of blocks, and applying an infinite impulse response filter to the image using the principle bilateral filtered image components. Other embodiments are disclosed.

Method and apparatus for image filtering

We investigate using a lattice and a staggered version of it for balanced multiple description quantization at high-resolution. By letting one side quantizer use a lattice codebook, and the other side quantizer use a codebook based on the same lattice with a slight shift, the joint quantizer as the central quantizer can naturally achieve a performance improvement over the side quantizers. Application of such a structure is meaningful when the side quantizers' distortions are of (equal) primary concern. Another immediate application of such a structure is when a refinement stage is added to further reduce the central distortion. We analyze the performance of this structure for these two applications, and then evaluate the root lattices A/sub n/, D/sub n/ (with dimension less than 9), E/sub 6/, E/sub 7/, E/sub 8/ and their duals. The results suggest that these two applications in fact lead to different choices of lattices: while the former requires good lattices in terms of their normalized second moments of inertia, the latter appears to perform better when the staggering of lattices generates more cells by intersection of the Voronoi regions of the two lattices. These observations also suggest a suboptimal but simple multiple description quantization scheme using lattices.

Staggered lattices in multiple description quantization

We consider the problem of upsampling a low-resolution depth map generated by a range camera, by using information
from one or more additional high-resolution vision cameras. The goal is to provide an accurate high resolution depth
map from the viewpoint of one of the vision cameras. We propose an algorithm that first converts the low resolution
depth map into a depth/disparity map through coordinate mappings into the coordinate frame of one vision camera, then
classifies the pixels into regions according to whether the range camera depth map is trustworthy, and finally refine the
depth values for the pixels in the untrustworthy regions. For the last refinement step, both a method based on graph cut
optimization and that based on bilateral filtering are examined. Experimental results show that the proposed methods
using classification are able to upsample the depth map by a factor of 10 x 10 with much improved depth details, with
significantly better accuracy comparing to those without the classification. The improvements are visually perceptible on
a 3D auto-stereoscopic display.

Upsampling range camera depth maps using high-resolution vision camera and pixel-level confidence classification

A three-layer scheme for M-channel multiple description image coding

We consider the multiuser successive refinement (MSR) problem, where the users are connected to a central server via links with different noiseless capacities, and each user wishes to reconstruct the source in a successive-refinement fashion. An achievable region is given for the two-user, two-layer case and it provides the complete rate-distortion region for the Gaussian source under the MSE distortion measure. The key observation is that this problem includes multiple description (MD) coding as a subsystem, and the techniques useful in the MD problem can be extended to this case. We show that the coding scheme based on the universality of random binning is sub-optimal, because multiple Gaussian side informations only at the decoders do incur performance loss, in contrast to the case of single side information at the decoder. We further show that unlike the single user case, when there are multiple users, the loss of performance by a multistage coding approach can be unbounded for the Gaussian source. The result suggests that in such a setting, the benefit of using successive refinement is not likely to justify the accompanying performance loss.

Chao Tian

Papers

Method and apparatus for image filtering

Staggered lattices in multiple description quantization

Upsampling range camera depth maps using high-resolution vision camera and pixel-level confidence classification

A three-layer scheme for M-channel multiple description image coding

Multiuser Successive Refinement and Multiple Description Coding