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Sorted region merging to maximize test reliability

We discuss an algorithmic approach to region merging which is built on a recent statistical work on the way to decide merging while keeping the complexity optimal. In that latter work, a concentration-based statistical test is proposed, having the particularity to reduce the error occurring when rejecting the merging of two observed regions coming from the same true region. We propose a preliminary ordered-based algorithmic procedure to cope with the errors occurring when merging two different regions in the first approach, thereby leading to a fast algorithm tailor-made for the reduction of both kinds of error. Experimentations proposed on images used without any preprocessing shed light on the quality of the segmentations obtained.