Titlebook: Geometrical Multiresolution Adaptive Transforms; Theory and Applicati Agnieszka Lisowska Book 2014 Springer International Publishing Switze

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https://doi.org/10.1007/978-94-007-6455-2 one is based on sliding multismoothlets. Both methods were compared to the state-of-the-art methods. As follows from the performed experiments, the method based on sliding multismoothlets leads to the best results of edge detection.

overture

Moments-Based Multismoothlet Transforme transform was presented in the consecutive steps, starting from a linear beamlet computation. Further, smoothlet parameters are computed. And finally, multismoothlet parameters are determined. At the end of this chapter, the computational complexity of the presented transform was discussed followed by some numerical results.

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Marcel Meinders,Nico Van Breemently to multiple edges. So, the multismoothlet can adapt to edges of different multiplicity, location, scale, orientation, curvature and blur. Additionally, a notion of sliding multismoothlet was introduced. It is the multismoothlet with location and size defined freely within an image. Based on that

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