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Found 2 papers, 1 papers with code
Blindly Deconvolving Super-noisy Blurry Image Sequences
In this paper, we consider multi-frame blind deconvolution (MFBD), where image blur is described by the convolution of an unobservable, undeteriorated image and an unknown filter, and the objective is to recover the undeteriorated image from a sequence of its blurry and noisy observations.
Superadditivity and Convex Optimization for Globally Optimal Cell Segmentation using Deformable Shape Models
In this work, we introduce a globally optimal approach based on deformable shape models and global energy minimization for cell nuclei segmentation and cluster splitting.
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