On the Use of Entropy Power for Threshold Selection

Franck Luthon (1) , Marc Liévin (2) , Francis Faux (1)

1 LIUPPA - Laboratoire Informatique de l'Université de Pau et des Pays de l'Adour
2 LIS - Laboratoire des images et des signaux

This paper deals with an entropic approach as unsupervised thresholding technique for image processing, in order to extract a relevant binary information from noisy data. It is dedicated to situations where a signal of relatively high energy is localized in the image whereas the noise is spread over the entire frame. The method is based on the computation of the entropy power of the information source, as defined by Shannon. The threshold used for binarization is proportional to the entropic deviation of the observation source. The performance of the approach is illustrated by two classical image preprocessing tasks, namely motion detection and edge detection. The evaluation set contains both synthetic data and real-world image sequences.

Keywords: automatic thresholding; binarization; entropic deviation; motion detection; edge detection; Gaussian noise

Domains: Signal and Image processing; Signal and Image Processing

Franck Luthon, Marc Liévin, Francis Faux. On the Use of Entropy Power for Threshold Selection. Signal Processing, 2004, 84, pp.1789-1804. ⟨hal-00408655⟩