Content-Aware Enhancement of Images With Filamentous Structures


Enhancement methods for photos with filamentous features are described in this research. For the elimination of clutter and noise from the backdrop, our method employs a gradient sparsity constraint coupled with a filamentous structure constraint. confocal microscopy photos of neurons, calcium imaging data, and photographs of road pavement are used to test the approach. We discovered that our method preserves both the structure and intensity of the original object in the improved photos. In neuron microscopy, we found that neurons increased by our method were better correlated with the original structure intensities than neurons improved by well-known methods. Calcium imaging data simulations show that both the number of neurons discovered and their accuracy have been increased. We discovered more regions of calcium activity in the entire field of vision when we applied our approach to real calcium data. Using our improvement method, we were able to detect smaller or milder cracks in road pavement.

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