Sparse Bayesian Learning of Filters for Efficient Image Expansion

Technology Used: Dot Net

2010

We propose a framework for expanding a given image using an interpolator that is trained in advance with training data, based on sparse Bayesian estimation for determining the optimal and compact support for efficient image expansion. Experiments on test data show that learned  interpolators are compact yet superior to classical ones.

4 thoughts on “Sparse Bayesian Learning of Filters for Efficient Image Expansion

  • August 31, 2011 at 6:17 pm
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    can u please elaborate and explain it what actually it is….. i needed it for my final year project..

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  • March 14, 2012 at 3:56 pm
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    send full project Sparse Bayesian Learning of Filters for Efficient Image Expansion with document and ppts to my mail

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  • July 14, 2012 at 4:27 pm
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    can u please elaborate this for my final year project

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