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Found 3 papers, 1 papers with code
DeepOrientation: convolutional neural network for fringe pattern orientation map estimation
Accurate estimation of the local fringe orientation map can significantly facilitate the measurement process on various ways, e. g., fringe filtering (denoising), fringe pattern boundary padding, fringe skeletoning (contouring/following/tracking), local fringe spatial frequency (fringe period) estimation and fringe pattern phase demodulation.
Physics-driven universal twin-image removal network for digital in-line holographic microscopy
Digital in-line holographic microscopy (DIHM) enables efficient and cost-effective computational quantitative phase imaging with a large field of view, making it valuable for studying cell motility, migration, and bio-microfluidics.
Versatile optimization-based speed-up method for autofocusing in digital holographic microscopy
We propose a speed-up method for the in-focus plane detection in digital holographic microscopy that can be applied to a broad class of autofocusing algorithms that involve repetitive propagation of an object wave to various axial locations to decide the in-focus position.
