Description:
Hop sparse Bayesian learning ( SBL ) and compressible sensing theory ( CS ) , give a compressible image reconstruction in the noise measurement conditions . The method of the CS theory image reconstruction process as a linear regression problem , the image to be reconstructed is unknown weighting parameters of the regression model towel SBL method to determine the weights given a priori probability distribution to limit the complexity of the model and the introduction of the hyper-parameters
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Image reconstruction method based on sparse Bayesian learning.pdf
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