Spatial information retrieval from remote-sensing images. I. Information theoretical perspective

Spatial statistical methods in health

“…In general, remote sensing and image processing techniques increasingly play a key role (e.g. see Datcu et al, 1998;Schroder et al, 1998;Stein et al, 1998b) as do advances in modelling of Markov Random Fields (e.g. see Aykroyd, 1998;Cressie & Davidson, 1998;Tjelmeland & Besag, 1998).…”

Expanding the Algorithmic Information Theory Frame for Applications to Earth Observation

“…Information theory has provided along the years several valuable tools for remote sensing applications, especially for model selection, texture extraction, distortion evaluation and informational content characterization of satellite images [1]. For specific applications, ideas derived from Shannon's theory have been applied to Synthetic Aperture Radar (SAR) data [2,3], and to derive similarity measures for spectral signatures acquired by hyperspectral sensors [4].…”

“…K(x|y) = min{|q| : U (< y, q >) = x} (1) where |q| is the size in bits of a program q ∈ Q. For the special case of y being the empty string ε, we rewrite the conditional complexity K(x|ε) simply as the complexity K(x), which can then be regarded as the size of the shortest computer program which outputs x if no auxiliary input is given to the computation [5].…”

Simple Traffic Surveillance System Based on Range-Doppler Radar Images

“…In [12], the issue of target classification to a level close to the identification is addressed. In [13], the basis for the automatic interpretation of images from sensors in general is approached, proposing a systematic approach to the interpretation of the scene present in the sensed image by the sensors. The results are applied to restoration of high-resolution SAR images.…”