Improved deblurring of images with guided image generation in W-DIP
Improved deblurring of images with guided image generation in W-DIP
Wiener Guided DIP for Unsupervised Blind Image Deconvolution
arXiv paper abstract https://arxiv.org/abs/2112.10271v1
arXiv PDF paper https://arxiv.org/pdf/2112.10271v1.pdf
Blind deconvolution is an ill-posed problem arising in various fields ranging from microscopy to astronomy.
The ill-posed nature of the problem requires adequate priors to arrive to a desirable solution.
Recently ... deep learning architectures can serve as an image generation prior during unsupervised blind deconvolution optimization,
however often exhibiting a performance fluctuation even on a single image.
... propose to use Wiener-deconvolution to guide the image generator during optimization by providing it a sharpened version of the blurry image using an auxiliary kernel estimate starting from a Gaussian.
... proposed method yields higher stability and performance across multiple datasets. ...
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