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文件名称:deblurring_demo-1.0

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    2013-07-04
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Bayesian Deblurring with Integrated Noise Estimation-Bayesian Deblurring with Integrated Noise Estimation

Conventional non-blind image deblurring algorithms

involve natural image priors and maximum a-posteriori

(MAP) estimation. As a consequence of MAP estimation,

separate pre-processing steps such as noise estimation and

training of the regularization parameter are necessary to

avoid user interaction. Moreover, MAP estimates involving

standard natural image priors have been found lacking in

terms of restoration performance. To address these issues

we introduce an integrated Bayesian framework that unifies

non-blind deblurring and noise estimation, thus freeing the

user of tediously pre-determining a noise level. A samplingbased

technique allows to integrate out the unknown noise

level and to perform deblurring using the Bayesian minimum

mean squared error estimate (MMSE), which requires

no regularization parameter and yields higher performance

than MAP estimates when combined with a learned highorder

image prior. A quan
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下载文件列表

deblurring_demo/
deblurring_demo/+learned_models/
deblurring_demo/+learned_models/cvpr_3x3_foe.m
deblurring_demo/+learned_models/cvpr_pw_mrf.m
deblurring_demo/+pml/
deblurring_demo/+pml/+distributions/
deblurring_demo/+pml/+distributions/@discrete/
deblurring_demo/+pml/+distributions/@discrete/discrete.m
deblurring_demo/+pml/+distributions/@discrete/eval.m
deblurring_demo/+pml/+distributions/@discrete/kl_divergence.m
deblurring_demo/+pml/+distributions/@discrete/mle.m
deblurring_demo/+pml/+distributions/@discrete/plot.m
deblurring_demo/+pml/+distributions/@discrete/private/
deblurring_demo/+pml/+distributions/@discrete/private/montecarlo.m
deblurring_demo/+pml/+distributions/@discrete/sample.m
deblurring_demo/+pml/+distributions/@discrete/semilogy.m
deblurring_demo/+pml/+distributions/@discrete/test/
deblurring_demo/+pml/+distributions/@discrete/test/test_all.m
deblurring_demo/+pml/+distributions/@foe/
deblurring_demo/+pml/+distributions/@foe/energy.m
deblurring_demo/+pml/+distributions/@foe/eval.m
deblurring_demo/+pml/+distributions/@foe/foe.m
deblurring_demo/+pml/+distributions/@foe/log_grad_x.m
deblurring_demo/+pml/+distributions/@foe/unnorm.m
deblurring_demo/+pml/+distributions/@gsm/
deblurring_demo/+pml/+distributions/@gsm/em.m
deblurring_demo/+pml/+distributions/@gsm/eval.m
deblurring_demo/+pml/+distributions/@gsm/gsm.m
deblurring_demo/+pml/+distributions/@gsm/log_grad_weights.m
deblurring_demo/+pml/+distributions/@gsm/log_grad_x.m
deblurring_demo/+pml/+distributions/@gsm/sample.m
deblurring_demo/+pml/+distributions/@gsm/test/
deblurring_demo/+pml/+distributions/@gsm/test/test_all.m
deblurring_demo/+pml/+distributions/@gsm/test/test_density.m
deblurring_demo/+pml/+distributions/@gsm/test/test_ho_derivatives.m
deblurring_demo/+pml/+distributions/@gsm/z_distribution.m
deblurring_demo/+pml/+distributions/@gsm_foe/
deblurring_demo/+pml/+distributions/@gsm_foe/cd.m
deblurring_demo/+pml/+distributions/@gsm_foe/energy_grad_J_tilde.m
deblurring_demo/+pml/+distributions/@gsm_foe/energy_grad_weights.m
deblurring_demo/+pml/+distributions/@gsm_foe/gsm_foe.m
deblurring_demo/+pml/+distributions/@gsm_foe/log_grad_theta.m
deblurring_demo/+pml/+distributions/@gsm_foe/private/
deblurring_demo/+pml/+distributions/@gsm_foe/private/estimator_helper.m
deblurring_demo/+pml/+distributions/@gsm_foe/sample_x.m
deblurring_demo/+pml/+distributions/@gsm_foe/sample_z.m
deblurring_demo/+pml/+distributions/@gsm_foe/test/
deblurring_demo/+pml/+distributions/@gsm_foe/test/test_density.m
deblurring_demo/+pml/+distributions/@gsm_foe/test/test_filter.m
deblurring_demo/+pml/+distributions/@gsm_foe/test/test_learning.m
deblurring_demo/+pml/+distributions/@gsm_foe/test/test_sampling.m
deblurring_demo/+pml/+distributions/@gsm_foe/z_distribution.m
deblurring_demo/+pml/+distributions/@gsm_pairwise_mrf/
deblurring_demo/+pml/+distributions/@gsm_pairwise_mrf/cd.m
deblurring_demo/+pml/+distributions/@gsm_pairwise_mrf/fit_precision.m
deblurring_demo/+pml/+distributions/@gsm_pairwise_mrf/gsm_pairwise_mrf.m
deblurring_demo/+pml/+distributions/@gsm_pairwise_mrf/log_grad_log_weights.m
deblurring_demo/+pml/+distributions/@gsm_pairwise_mrf/private/
deblurring_demo/+pml/+distributions/@gsm_pairwise_mrf/private/estimator_helper.m
deblurring_demo/+pml/+distributions/@gsm_pairwise_mrf/test/
deblurring_demo/+pml/+distributions/@gsm_pairwise_mrf/test/test_density.m
deblurring_demo/+pml/+distributions/@gsm_pairwise_mrf/test/test_learning.m
deblurring_demo/+pml/+distributions/@gsm_pairwise_mrf/test/test_statistics.m
deblurring_demo/+pml/+distributions/@pairwise_mrf/
deblurring_demo/+pml/+distributions/@pairwise_mrf/pairwise_mrf.m
deblurring_demo/+pml/+distributions/density.m
deblurring_demo/+pml/+distributions/distribution.m
deblurring_demo/+pml/+image_proc/
deblurring_demo/+pml/+image_proc/convmtxn.m
deblurring_demo/+pml/+image_proc/imfiltermtx.m
deblurring_demo/+pml/+image_proc/make_convn_mat.m
deblurring_demo/+pml/+image_proc/make_imfilter_mat.m
deblurring_demo/+pml/+image_proc/psnr.m
deblurring_demo/+pml/+image_proc/ssim_index.m
deblurring_demo/+pml/+numerical/
deblurring_demo/+pml/+numerical/checkgrad.m
deblurring_demo/+pml/+numerical/minimize.m
deblurring_demo/+pml/+numerical/sle_spd_solver.m
deblurring_demo/+pml/+support/
deblurring_demo/+pml/+support/assemble_images.m
deblurring_demo/+pml/+support/epsr.m
deblurring_demo/+pml/+support/mirror_boundary.m
deblurring_demo/+pml/+support/nefdims.m
deblurring_demo/+pml/+support/randi.m
deblurring_demo/CHANGELOG
deblurring_demo/Contents.m
deblurring_demo/LICENSE
deblurring_demo/README
deblurring_demo/restoration/
deblurring_demo/restoration/blurkernel-levinetal.mat
deblurring_demo/restoration/deblur_mmse.m
deblurring_demo/restoration/demo_deblurring.m
deblurring_demo/restoration/demo_denoising.m
deblurring_demo/restoration/images/
deblurring_demo/restoration/images/barbara.png
deblurring_demo/restoration/images/boat.png
deblurring_demo/restoration/images/fingerprint.png
deblurring_demo/restoration/images/house.png
deblurring_demo/restoration/images/lena.png
deblurring_demo/restoration/images/peppers256.png
deblurring_demo/restorat

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