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Image Transformation Based on Learning Dictionaries across Image Spaces
2013
IEEE Transactions on Pattern Analysis and Machine Intelligence
In this paper, we propose a framework of transforming images from a source image space to a target image space, based on learning coupled dictionaries from a training set of paired images. The framework can be used for applications such as image super-resolution, and estimation of image intrinsic components (shading and albedo). It is based on a local parametric regression approach, using sparse feature representations over learned coupled dictionaries across the source and target image spaces.
doi:10.1109/tpami.2012.95
pmid:22529324
fatcat:b26jvrj4w5g3tpt2ayqpru4nru