We present a new clustering algorithm called k-means-u* which in many cases is able to significantly improve the clusterings found by k-means++, the current de-facto standard for clustering in Euclidean spaces. First we introduce the k-means-u algorithm which starts from a result of k-means++ and attempts to improve it with a sequence of non-local “jumps” alternated by runs of standard k-means....

The multiplicative nature of speckle noise present in imaging modalities like echocardiography complicates the despeckling procedure as it would be necessary to remove noise with the edges well preserved. A novel speckle reduction technique based on integration of moving average filter using fuzzy triangulation membership function (TMAV) with moving average center with wiener filter is proposed...