Scaled Heavy Ball Acceleration of the Richardson Lucy Algorithm for 3D Microscopy Image Restoration - 2014 PROJECT TITLE : Scaled Heavy Ball Acceleration of the Richardson Lucy Algorithm for 3D Microscopy Image Restoration - 2014 ABSTRACT: The Richardson-Lucy algorithm is one of the foremost vital in image deconvolution. However, a downside is its slow convergence. A important acceleration was obtained using the technique proposed by Biggs and Andrews (BA), which is implemented in the deconvlucy function of the Image Processing MATLAB toolbox. The BA technique was developed heuristically with no proof of convergence. In this paper, we have a tendency to introduce the heavy-ball (H-B) technique for Poisson information optimization and extend it to a scaled H-B technique, which includes the BA technique as a special case. The strategy features a proof of the convergence rate of O(K-two), where k is the quantity of iterations. We have a tendency to demonstrate the superior convergence performance, by a speedup issue of 5, of the scaled H-B method on both synthetic and real 3D pictures. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Deconvolution Stochastic Processes Optimisation Iterative Methods Image Restoration Poisson Noise Richardson-Lucy Algorithm Heavy-Ball Acceleration Context-Aware Discovery of Visual Co-Occurrence Patterns - 2014 Novel Speed Up Strategies for Non-Local Means Denoising With Patch and Edge Patch Based Dictionaries - 2014
