Super resolution the one pass example based algo rithm gives the enlargements in figures 2h and 2i our algorithm requires only a nearest neighbor search in the training set for a vector derived from each patch of local image data this one pass super resolution algorithm is a step toward achieving resolution independence in. This one pass super resolution algorithm is a step toward achieving resolution independence in image based representations we dont expect perfect resolution independence even the polygon representation doesnt have that but increasing the resolution independence of pixel based representations is an important task for ibr. Example based super resolution provides a thorough introduction and overview of example based super resolution covering the most successful algorithmic approaches and theories behind them with implementation insights it also describes current challenges and explores future trends readers of this book will be able to understand the latest natural image patch statistical models and the . Abstract this chapter presents example based super resolution as a family of techniques alternative to classic multiframe super resolution example based approaches include parametric methods which are not covered by this book and nonparametric ones which typically build on existing machine learning techniques. This method has a potential to advance the way by which images are obtained in super resolution microscopy thereby significantly improving temporal resolution example based resolution
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