New measure of contrast: the dynamics

Michel Grimaud

doi:10.1117/12.60650

1 June 1992 New measure of contrast: the dynamics

Michel Grimaud

Proceedings Volume 1769, Image Algebra and Morphological Image Processing III; (1992) https://doi.org/10.1117/12.60650
Event: San Diego '92, 1992, San Diego, CA, United States

Abstract

On a grey level image, extrema correspond to zones of uniform altitude whose neighboring pixels have a strictly lower (maxima) or strictly higher (minima) altitude. If an image is seen as a relief, minima are located at the bottom of valleys or pits (structures darker than the background) and maxima are located at the top of plateaus, pics, or domes (structures lighter than the background). The detection of extrema is often used as the first step of a segmentation process when we just need to roughly located objects of interest. Unfortunately, the noise sensitivity of this transformation makes it uneasy to use. We propose in this paper a transformation which valuates the extrema on a contrast criterion: the dynamics. The selection of the minima of interest is easier with this contrast information. The dynamics is a measure at the scale of the structure. It does not characterize the extremum itself or its catchment basin but the structure containing the extremum. An original aspect of the dynamics is that this transformation does not consider the size and the shape of the structures. We do not need to know a priori the size of the structures to evaluate their contrast. That is not the case for contrast feature extraction like the top-hat transformation. The computation of the dynamics is not straight forward from its definition. We propose a technique of computation based on flooding simulations. Using last algorithmical developments, this implementation is particularly efficient. That will help to develop the use of the promising transformations based on the dynamics.

Citation Download Citation

Michel Grimaud "New measure of contrast: the dynamics", Proc. SPIE 1769, Image Algebra and Morphological Image Processing III, (1 June 1992); https://doi.org/10.1117/12.60650

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