Abstract
Photographs of text documents taken by hand-held cameras can be
easily degraded by camera motion during exposure. In this paper, we propose a
new method for blind deconvolution of document images. Observing that document
images are usually dominated by small-scale high-order structures, we propose
to learn a multi-scale, interleaved cascade of shrinkage fields model,
which contains a series of high-order filters to facilitate joint recovery of blur
kernel and latent image. With extensive experiments, we show that our method
produces high quality results and is highly efficient at the same time, making it
a practical choice for deblurring high resolution text images captured by modern
mobile devices.
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