Extraction of diffuse objects from images by means of watershed and region merging: example of solar images

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
Mariusz Nieniewski

Abstract

This paper presents a new method for extraction of diffuse objects from images, which was developed for segmentation of solar images obtained from extreme-UV imaging telescope (EIT) experiments of the satellite SOHO mission. As a particular type of objects to be extracted coronal holes in EIT images have been chosen. The method described is based on the use of a watershed algorithm. The result of the watershed segmentation is a partition of the whole domain of the image into a large number of small regions. These regions are then combined in a region merging process. The proposed region merging algorithm iteratively adds the darkest regions and maximizes the average contrast between a current mask and a set of its neighboring regions. We show that the maximization of the average contrast gives segmentation results that are visually acceptable. Furthermore, this approach allows us to conduct the segmentation of EIT images independently of any explicit fine-tuning parameters. The proposed method was extensively tested on EIT images obtained at various times and various levels of solar activity, and we will show that it can be used independently of the local brightness level and the extent of coronal holes.

References

Feb 8, 2008·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·A Trémeau, P Colantoni
Feb 12, 2008·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·J M Gauch
Jan 1, 1997·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·L ShafarenkoJ Kittler

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Citations

Nov 16, 2016·Journal of Digital Imaging·Marcin Ciecholewski

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