Iterative area filtering of multichannel images

Owing to the absence of total ordering between vectors of more than one dimension, most morphological transformations are not directly applicable to multichannel images. In this paper, we show that area based operators can be extended to the processing of multichannel images by using the quasi-flat zones and seeded region growing paradigms. The method is iterative in the sense that it starts with the smallest non-unitary quasi-flat zones until an automatically derived contrast threshold value is reached. Pseudo-code is given for all algorithms. We illustrate their usefulness for the simplification of complex natural images such as those occurring in satellite images of the earth.