Generic lossy image compression algorithms, such as Said & Pearlman's, perform excellently on gridded terrain elevation data. For example, an average DEM compressed down to 0.1 bits per point has an RMS elevation error of 3 meters, although di erent DEMs ranged from 0.25 to 15 meters. This performance compares favorably to compressing with Triangulated Irregular Networks. Preliminary tests also...

Computational techniques are frequently used to compress image data so that transmission and storage requirements are reduced. If the computational techniques result in no loss in image resolution, the technique is referred to as lossless compression. Greater compression of data may yield some loss in spatial or temporal resolution, and is referred to as lossy compression. In some radiologic ex...

An analytic model is presented for a partially reliable transport protocol based on retransmissions. The model illustrates tradeo s between two QoS parameters (delay and throughput), and various levels of reliability. The model predicts that the use of reliable transport service when an application only needs a partially reliable one causes considerable throughput decreases and delay increases ...

In this paper a new image transformation suited for reversible (lossless) image compression is presented. It uses a simple pyramid multiresolution scheme which is enhanced via predictive coding. The new transformation is similar to the subband decomposition, but it uses only integer operations. The number of bits required to represent the transformed image is kept small though careful scaling a...

In recent years, wireless networks have become increasingly common and an increasing number of devices are communicating with each other over lossy links. Unfortunately, TCP performs poorly over lossy links as it is unable to differentiate the loss due to packet corruption from that due to congestion. In this paper, we present an extension to TCP which enables TCP to distinguish packet corrupti...

We draw a certain analogy between the classical information–theoretic problem of lossy data compression (source coding) of memoryless information sources and the statistical mechanical behavior of a certain model of a chain of connected particles (e.g., a polymer) that is subjected to a contracting force. The free energy difference pertaining to such a contraction turns out to be proportional t...

We study electromagnetic properties of periodic composite structures, such as photonic crystals, involving lossy components. We show that in many cases a properly designed periodic structure can dramatically suppress the losses associated with the absorptive component, while preserving or even enhancing its useful functionality. As an example, we consider magnetic photonic crystals, in which th...

Classical minimum entropy set cover problem relies on the finding the most likely assignment between the set of observations and the given set of their types. The solution is described by such partition of data space which minimizes the entropy of the distribution of types. The problem finds a natural application in the machine learning, clustering and data classification. In this paper we show...