Image Restoration and Topological Optimization

Image Restoration via Topological Derivative

Constrained optimization of image restoration filters.

A linear shift-invariant preprocessing technique is described which requires no specific knowledge of the image parameters and which is sufficiently general to allow the effective radius of the composite imaging system to be minimized while constraining other system parameters to remain within specified limits.

Approximation and Optimization in Image Restoration and Reconstruction

We will present a convex representation for the minimal partition problem, based on the notion of “paired calibrations” [2], [3]. We propose an efficient algorithm for minimizing this problem, and discuss the practical implementation with “many” labels. It can be applied to a number of problems, from segmentation to stereo reconstruction. The quality of the results is substantially better than ...

Approximation and Optimization in Image Restoration and Reconstruction

X-ray computed tomography (CT) performs adequately in the vast majority of clinical situations. However, in specific cases, it falls short of the required precision (e.g., for characterization of very small structures or in the presence of highly absorbing materials). In order to overcome these difficulties, it is generally necessary to cast the reconstruction problem in an estimation framework...

Approximation and Optimization in Image Restoration and Reconstruction

Traditional wavelets have a number of vanishing moments that corresponds to their equivalent order of the derivation. They offer good energy compaction for piecewise smooth signals, but are less appropriate for more complex signals such as those originating in functional imaging ; e.g., the hemodynamic response after brain activation in functional magnetic resonance imaging (fMRI) and time acti...