This paper presents a new, fully automatic and robust feature extraction algorithm based on the selection of a given range of scales. It compares consecutive band-pass images of a Gaussian multiscale decomposition to extract the objects that appear between given scales. The comparison is performed using original distributed entropy measures. The application to building detection in aerial images shows that scale is a robust and precise criterion for the detection of man-made objects. They also show that distributed entropic tools are relevant for the comparison of band-pass images. From a more theoretical point of view, this method stands between the scale-space and wavelet approaches. It tries to infer the geometrical concept of scale found in the scale-space theory into the algebraic scale of the wavelet theory.
['Alexandre Winter', 'Henri Maître', 'Nicole Cambou', 'Eric Legrand']
Entropy and multiscale analysis: a new feature extraction algorithm for aerial images