论文信息 - Ensemble Learning for Blind Image Separation and Deconvolution

Ensemble Learning for Blind Image Separation and Deconvolution

In this chapter, ensemble learning is applied to the problem of blind source separation and deconvolution of images. It is assumed that the observed images were constructed by mixing a set of images (consisting of independent, identically distributed pixels), convolving the mixtures with unknown blurring filters and then adding Gaussian noise.

David J. C. MacKay | James W. Miskin | D. Mackay | J. W. Miskin | D. MacKay

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