A water supply infrastructures application of change detection by measuring spectral change features

In the last years, the extraction of the information content from digital images has assumed a crucial role in many application fields, such as risk assessment, analysis of damages, deforestation, environmental monitoring, earth observation, as a fundamental instrument to carry out specific and pointed studies. In this context the change detection of remotely sensed images takes place. Detecting changes means performing a spatial comparison of two or more images acquired over the same geographical area at different times. This operation can be performed on a per-pixel basis as well as on a per-object basis, depending on the aim of the specific application. In particular, in this paper two versions of the same change detection algorithm are presented, the one working on a per-pixel basis while the other working on an per-object basis, applied specifically for the monitoring of a water supply infrastructure. This algorithm provides the changes occurred in optical images' spectral content, as well as in their radiance content, by calculating two change features: the spectral angle made by two corresponding spectral vectors in the compared images, and the so-called Brightness Change Factor. The object-based version of the presented change detection algorithm has been developed according to an IIM - Image Information Mining context, in order to introduce an automated procedure to detect changes; furthermore, it has been developed with an a image analysis framework, called IPAINT - Image Processing Analysis Interpretation and Trasconding, which can be used for various applications thanks to its versatility, since it offers many different techniques for image processing.

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