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Robust Source Coding of Images for Very Noisy Channels
 I. INTRODUCTION In environments where the
, 1999
"... Robust source coding provides the compression and noise mitigation necessary for image transmission over noisy channels. Here two methods are compared, DPCM and PTCQ, both incorporating linear and nonlinear filters. Findings show that although PTCQ has better ratedistortion properties, the DPCM ..."
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Cited by 1 (0 self)
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Robust source coding provides the compression and noise mitigation necessary for image transmission over noisy channels. Here two methods are compared, DPCM and PTCQ, both incorporating linear and nonlinear filters. Findings show that although PTCQ has better ratedistortion properties, the DPCM
Robust Source Coding with Generalised Tcodes
, 1998
"... This thesis presents a range of novel and improved results in the area of source coding with TCodes, based on a thorough review of the recursive structure of the TCodes. TCodes were introduced by Mark Titchener in 1984. They are variablelength codes, similar to the wellknown Huffman codes and m ..."
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This thesis presents a range of novel and improved results in the area of source coding with TCodes, based on a thorough review of the recursive structure of the TCodes. TCodes were introduced by Mark Titchener in 1984. They are variablelength codes, similar to the wellknown Huffman codes
On ErrorRobust Source Coding with Image Coding Applications
"... This thesis treats the problem of source coding in situations where the encoded data is subject to errors. The typical scenario is a communication system, where source data such as speech or images should be transmitted from one point to another. A problem is that most communication systems introduc ..."
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This thesis treats the problem of source coding in situations where the encoded data is subject to errors. The typical scenario is a communication system, where source data such as speech or images should be transmitted from one point to another. A problem is that most communication systems
Robust Source Coding For Images Over Very Noisy Channels
"... Robust source coding provides both compression and noise mitigation without channel coding. In this paper, two methods of robust source coding are presented. The first is DPCM incorporating a nonlinear filter; the second is Predictive TrellisCoded Quantization (PTCQ), whose prediction filter is als ..."
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Robust source coding provides both compression and noise mitigation without channel coding. In this paper, two methods of robust source coding are presented. The first is DPCM incorporating a nonlinear filter; the second is Predictive TrellisCoded Quantization (PTCQ), whose prediction filter
Robust source coding with first order Multiplexed Codes: construction and soft decoding
, 2003
"... This paper addresses the problem of design of variable length codes (VLC) that would allow to exploit higherorder source statistics while still being resilient to transmission errors. The codes introduced extend and generalize the family of codes called multiplexed codes, referred to as stationary ..."
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This paper addresses the problem of design of variable length codes (VLC) that would allow to exploit higherorder source statistics while still being resilient to transmission errors. The codes introduced extend and generalize the family of codes called multiplexed codes, referred to as stationary
Network Coding for Large Scale Content Distribution
"... We propose a new scheme for content distribution of large files that is based on network coding. With network coding, each node of the distribution network is able to generate and transmit encoded blocks of information. The randomization introduced by the coding process eases the scheduling of bloc ..."
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Cited by 493 (7 self)
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of the original file) and, also, to schemes in which only the source is allowed to generate and transmit encoded packets. We study the performance of network coding in heterogeneous networks with dynamic node arrival and departure patterns, clustered topologies, and when incentive mechanisms to discourage free
Bandera: Extracting Finitestate Models from Java Source Code
 IN PROCEEDINGS OF THE 22ND INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING
, 2000
"... Finitestate verification techniques, such as model checking, have shown promise as a costeffective means for finding defects in hardware designs. To date, the application of these techniques to software has been hindered by several obstacles. Chief among these is the problem of constructing a fini ..."
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Cited by 654 (33 self)
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program source code. Bandera takes as input Java source code and generates a program model in the input language of one of several existing verification tools; Bandera also maps verifier outputs back to the original source code. We discuss the major components of Bandera and give an overview of how it can
The ratedistortion function for source coding with side information at the decoder
 IEEE Trans. Inform. Theory
, 1976
"... AbstractLet {(X,, Y,J}r = 1 be a sequence of independent drawings of a pair of dependent random variables X, Y. Let us say that X takes values in the finite set 6. It is desired to encode the sequence {X,} in blocks of length n into a binary stream*of rate R, which can in turn be decoded as a seque ..."
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Cited by 1060 (1 self)
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AbstractLet {(X,, Y,J}r = 1 be a sequence of independent drawings of a pair of dependent random variables X, Y. Let us say that X takes values in the finite set 6. It is desired to encode the sequence {X,} in blocks of length n into a binary stream*of rate R, which can in turn be decoded as a sequence { 2k}, where zk E %, the reproduction alphabet. The average distorjion level is (l/n) cl = 1 E[D(X,,z&, where D(x, $ 2 0, x E I, 2 E J, is a preassigned distortion measure. The special assumption made here is that the decoder has access to the side information {Yk}. In this paper we determine the quantity R*(d). defined as the infimum of rates R such that (with E> 0 arbitrarily small and with suitably large n) communication is possible in the above setting at an average distortion level (as defined above) not exceeding d + E. The main result is that R*(d) = inf[Z(X,Z) Z(Y,Z)], where the infimum is with respect to all auxiliary random variables Z (which take values in a finite set 3) that satisfy: i) Y,Z conditiofally independent given X; ii) there exists a functionf: “Y x E +.%, such that E[D(X,f(Y,Z))] 5 d. Let Rx, y(d) be the ratedistortion function which results when the encoder as well as the decoder has access to the side information {Y,}. In nearly all cases it is shown that when d> 0 then R*(d)> Rx, y(d), so that knowledge of the side information at the encoder permits transmission of the {X,} at a given distortion level using a smaller transmission rate. This is in contrast to the situation treated by Slepian and Wolf [5] where, for arbitrarily accurate reproduction of {X,}, i.e., d = E for any E> 0, knowledge of the side information at the encoder does not allow a reduction of the transmission rate.
Robust realtime face detection
 International Journal of Computer Vision
, 2004
"... We have constructed a frontal face detection system which achieves detection and false positive rates which are equivalent to the best published results [7, 5, 6, 4, 1]. This face detection system is most clearly distinguished from previous approaches in its ability to detect faces extremely rapidly ..."
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Cited by 1888 (9 self)
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rates. Our system achieves high frame rates working only with the information present in a single grey scale image. These alternative sources of information can also be integrated with our system to achieve even higher frame rates.
Results 1  10
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1,271,467