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Contrast enhancement and image segmentation using a class of morphological nonincreasing filters

In this paper, contrast enhancement and image segmentation are investigated using a class of morphological nonincreasing filters that can be considered toggle mappings. These nonincreasing filters are built using the traditional morphological gradients. These filters have interesting properties and give essential contrast to the images. We apply them sequentially between two or more given 
parameters in order to obtain intermediate results. This approach improves the control of the filtering process and provides other tools for contrasting images. We presented several new properties and 
one study of the invariant set of these filters. Using these new propositions, we show that it is possible to obtain better results in image segmentation when we apply the watershed transformation. 
Also, we propose an algorithm for segmenting images using this class of nonincreasing filters. The method is applied in a geodesic way using two different criteria for segmenting an image. We relate our results with a recent method in mathematical morphology called the flat zone approach and we compare our approach with another method in image processing, the so-called quadtree approach.