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We provide bounds to the rate distortion tradeoff of the binary Markov source with the Hamming distance as the distortion measure. The tradeoff has been completely characterized by Gray (1970) for distortions less than a critical value Dc. Our motivation is to examine the tradeoff for values of distortion above Dc. Our inner bound to the tradeoff follows from an achievable scheme that uses conditional...
This paper presents a technique that aims at reducing the expansion of the compressed files that is caused by the multiplicity of equivalent messages. It does not try to eliminate multiplicity. Instead, it takes advantage of multiplicity by converting it into useful information, which we choose to describe parts of the compressed file itself. We call this technique bit recycling. On the decompressor...
The Standard for the Exchange of Earthquake Data (SEED) is a commonly used file format for recording seismographic data. The data description language (DDL) is part of the specification of the SEED format; it is used to describe the way in which the data has been encoded in the SEED file. All SEED files contain a piece of DDL code that describes how to read the data contained in the file. In this...
The problem of transmitting an analog source over a quasi-static fading channel is considered. This problem is motivated by the recent demand for multimedia content over wireless channels. The goal is to minimize the expected distortion of the received signal. An efficient numerical technique is proposed to explicitly solve the rate and power allocation problems at a finite SNR. The proposed algorithm...
In this paper, a globally distortion optimal solution is proposed for FPP. The method, which is applicable to any source with arbitrary distortion-rate characteristics, has quadratic complexity in N, where N is the number of transmitted packets. It is based on constructing a search trellis in which trellis levels represent the number of packets, trellis states at a given level i embody the possible...
This paper addresses the problem of building a compact representation of objects which enables to define a similarity measure. The key idea is to provide a mean to extract and represent the relevant information of an object. By integrating the minimum length description to an informational similarity metric, a new informational measure is proposed based on models. First, we make the strong assumption...
Compressive sensing (CS) is a new signal acquisition technique for sparse and compressible signals. Rather than uniformly sampling the signal, CS computes inner products with randomized basis functions; the signal is then recovered by a convex optimization. Random CS measurements are universal in the sense that the same acquisition system is sufficient for signals sparse in any representation. This...
Only summary form given.Java has been introduced to the mobile/wireless handsets and Java enabled handsets are now prevalent in the market, showing their successful launch. A variety of attractive services have been developed and promise a lot of fun to our daily lives, which are however targeted to the high end products that are very expensive. We focus on economic types with similar performance...
Distributed compression is particularly attractive for stereo images since it avoids communication between cameras. Since compression performance depends on exploiting the redundancy between images, knowing the disparity is important at the decoder. Unfortunately, distributed encoders cannot calculate this disparity and communicate it. We consider the compression of grayscale stereo images, and develop...
Many scientific, imaging, and geospatial applications produce large high-precision scalar fields sampled on a regular grid. Lossless compression of such data is commonly done using predictive coding, in which weighted combinations of previously coded samples known to both encoder and decoder are used to predict subsequent nearby samples. In hierarchical, incremental, or selective transmission, the...
We address the problem of a finite delay constraint in an arithmetic coding system. Due to the nature of the arithmetic coding process, source sequences causing arbitrarily large encoding or decoding delays exist. Therefore, to meet a finite delay constraint, it is necessary to intervene with the normal flow of the coding process, e.g., to insert fictitious symbols. This results in an inevitable coding...
In this paper, we propose an dictionary-based English text compression algorithm; we name it star word ending (StarWE) because of certain similarities to the StarNT algorithm. Furthermore, StarWE borrows techniques that are used in WRT such as EOL coding, punctuation mark modeling, and n-gram matching. The main difference between StarWE and StarNT is in the division of the external dictionary; StarWE...
This paper describes the Samplify family of lossless and lossy real-time compression algorithms for FPGAs and ASICs, operating at rates up to 40 Gsamp/sec, which achieve efficient, cost-effective compression of between 2:1 and 8:1. Compression for measurements reduces bandwidth and storage requirements in automated test equipment (ATE), medical imaging, oscilloscope, and other mixed-signal test applications.
The extensible markup language XML has become indispensable in many areas, but a significant disadvantage is its size: tagging a set of data increases the space needed to store it, the bandwidth needed to transmit it, and the time needed to parse it. We present a new compression technique based on the document type, expressed as a Relax NG schema. Assuming the sender and receiver agree in advance...
We present a simple lossless audio codec, composed of an integer-reversible modulated lapped transform (MLT) followed by a backward-adaptive run-length/Golomb-Rice (RLGR) encoder. Its compression performance matches those of state-of-the-art predictive codecs, and it has the advantage that its compressed bitstream contains frequency-domain data that can be used for applications such as search, identification,...
In this paper we propose an optimal joint source channel decoder (JSCD) for two mutually correlated sources each having memory that can be represented by first order Markov processes, and are transmitted through channels with memory representing slow fading wireless channels. We use the additive Markov channel (AMC) model and multiple access source codes (MASC)
In this work we consider dimension reducing mappings that can be used for joint source-channel coding (JSCC) systems. In such systems, the source coding and the channel coding is performed as a single operation. Although it is known by Shannon's separation theorem that asymptotically JSCC is not required for attaining the optimal performance, utilizing such schemes is beneficial for practical reasons...
In this paper presents a video-coding system that does not perform explicit ME/MC but instead relies on the DDWT to isolate moving signal features. To counteract the redundancy of the DDWT, a noise-shaping process increases the sparsity of the transform coefficients, resulting in a high degree of spatiotemporally coherent regions of insignificant coefficients. The transform coefficients are coded...
The following topics were dealt with: stochastic video model; half-pel accurate motion-compensated orthogonal video transforms; spatial sparsity induced temporal prediction; hybrid video compression; order-1 normalized maximum likelihood model; DNA sequence compression; biological sequence compression; structure induction; lossless graph compression; multiple-description coding; dithered delta-sigma...
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