• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Tools

Sorted by:
Try your query at:
Semantic Scholar Scholar Academic
Google Bing DBLP
Results 1 - 10 of 460
Next 10 →

vic: A Flexible Framework for Packet Video

by Steven Mccanne, Van Jacobson - ACM Multimedia , 1995
"... The deployment of IP Multicast has fostered the development of a suite of applications, collectively known as the MBone tools, for real-time multimedia conferencingover the Internet. Two of these tools --- nv from Xerox PARC and ivs from INRIA --- provide video transmission using softwarebased codec ..."
Abstract - Cited by 369 (18 self) - Add to MetaCart
, and support for diverse compression algorithms. We also propose a novel compression scheme called "IntraH. 261". Created as a hybrid of the nv and ivs codecs, IntraH. 261 provides a factor of 2-3 improvement in compression gain over the nv encoder (6 dB of PSNR) as well as a substantial improvement

Coil sensitivity encoding for fast MRI. In:

by Klaas P Pruessmann , Markus Weiger , Markus B Scheidegger , Peter Boesiger - Proceedings of the ISMRM 6th Annual Meeting, , 1998
"... New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect complementa ..."
Abstract - Cited by 193 (3 self) - Add to MetaCart
New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect

Compressive radar imaging

by Richard Baraniuk - Proc. 2007 IEEE Radar Conf , 2007
"... Abstract—We introduce a new approach to radar imaging based on the concept of compressive sensing (CS). In CS, a low-dimensional, nonadaptive, linear projection is used to acquire an efficient representation of a compressible signal directly using just a few measurements. The signal is then reconstr ..."
Abstract - Cited by 108 (8 self) - Add to MetaCart
Abstract—We introduce a new approach to radar imaging based on the concept of compressive sensing (CS). In CS, a low-dimensional, nonadaptive, linear projection is used to acquire an efficient representation of a compressible signal directly using just a few measurements. The signal

Encoding Binary Images using Cellular Automata for Data Compression

by Nashat G. Al Bdour
"... In this paper, I propose a method for efficient coding of images using cellular automata. This method allows us to describe each selected group of neighboring cells of bend points in the contour. This method enables us to compress the image code. These groups will be separated to objects in an image ..."
Abstract - Add to MetaCart
In this paper, I propose a method for efficient coding of images using cellular automata. This method allows us to describe each selected group of neighboring cells of bend points in the contour. This method enables us to compress the image code. These groups will be separated to objects

Cellular Automata: Algorithms and Applications

by Adam Clarridge , 2009
"... Cellular automata (CA) are an interesting computation medium to study because of their simplicity and inherently parallel operation. These characteristics make them a useful and efficient computation tool for applications such as cryptography and physical systems modelling, particularly when impleme ..."
Abstract - Add to MetaCart
components. We show that, under certain technical assump-tions, a marker cellular automaton has a unique inverse with a given neighbourhood. We use these results to develop a working key generation algorithm for a public-key cryptosystem based on reversible cellular automata originally conceived by Kari. We

An architecture for compressive imaging

by Michael B. Wakin, Jason N. Laska, Marco F. Duarte, Dror Baron, Shriram Sarvotham, Dharmpal Takhar, Kevin F. Kelly, Richard G. Baraniuk - in IEEE International Conference on Image Processing (ICIP , 2006
"... Compressive Sensing is an emerging field based on the revelation that a small group of non-adaptive linear projections of a compressible signal contains enough information for reconstruction and processing. In this paper, we propose algorithms and hardware to support a new theory of Compressive Imag ..."
Abstract - Cited by 87 (7 self) - Add to MetaCart
Compressive Sensing is an emerging field based on the revelation that a small group of non-adaptive linear projections of a compressible signal contains enough information for reconstruction and processing. In this paper, we propose algorithms and hardware to support a new theory of Compressive

Hardware Implementation on FPGA Platform for Cellular Automata Cryptosystem

by Eduard Franti, Monica Dascalu
"... Abstract:- This paper presents a complex project that aims the development and design of a parallel computing based cryptographic system. Cryptography is a field of major scientific and technical interest nowadays, mainly because of the increased security demands of different communication systems. ..."
Abstract - Add to MetaCart
. The novelty and the main interest in this project is the orientation towards the hardware implementation. Special software has been developed for the analysis of different encryption/decryption strategies with cellular automata. Between the various strategies and algorithms studied, the best were selected

Resolution Scalable Image Coding with Reversible Cellular Automata

by Lorenzo Cappellari , Member, IEEE Simone Milani , Student Member, IEEE Carlos Cruz-Reyes , Member, IEEE Giancarlo Calvagno
"... Abstract-In a resolution scalable image coding algorithm, a multiresolution representation of the data is often obtained using a linear filter bank. Reversible cellular automata have been recently proposed as simpler, non-linear filter banks that produce a similar representation. The original image ..."
Abstract - Add to MetaCart
, the proposed algorithm that uses simple local rules compares well with the JBIG compression standard, in particular for images where the foreground is made of a simple connected region. For complex images, more efficient local rules based on the lifting principle have been designed. They provide compression

GPU Accelerated Computation and Visualization of Hexagonal Cellular Automata

by Stéphane Gobron, Hervé Bonafos, Daniel Mestre
"... We propose a graphics processor unit (GPU)-accelerated method for real-time computing and rendering cellular automata (CA) that is applied to hexagonal grids. Based on our previous work [9] –which introduced first and second dimensional cases – this paper presents a model for hexagonal grid algorith ..."
Abstract - Cited by 5 (1 self) - Add to MetaCart
We propose a graphics processor unit (GPU)-accelerated method for real-time computing and rendering cellular automata (CA) that is applied to hexagonal grids. Based on our previous work [9] –which introduced first and second dimensional cases – this paper presents a model for hexagonal grid

Cryptosystems Based on Reversible Cellular Automata

by Jarkko Kari , 1992
"... We propose the use of reversible cellular automata (RCA) as efficient encryption and decryption devices. The efficiency is due to their inherent parallelism. They can be used both as classical secret-key cryptosystems and as public-key systems. 1 Introduction The low speed of encryption and/or ..."
Abstract - Cited by 16 (0 self) - Add to MetaCart
We propose the use of reversible cellular automata (RCA) as efficient encryption and decryption devices. The efficiency is due to their inherent parallelism. They can be used both as classical secret-key cryptosystems and as public-key systems. 1 Introduction The low speed of encryption and
Next 10 →
Results 1 - 10 of 460
Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University