2023/05/17 by Julianna Winnik, Damian Suski, Winnik, Julianna +9
Engineering · Immunology and Microbiology · Physics and Astronomy · #Digital Holography and Microscopy #FOS: Biological sciences #FOS: Electrical engineering #FOS: Physical sciences #Image Processing Techniques and Applications #Image and Video Processing (eess.IV) #Immunotherapy and Immune Responses #Optics (physics.optics) #Quantitative Methods (q-bio.QM) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2305.10606
openalex publication_date 2023/05/17 · openalex created_date 2023/05/21 · openalex updated_date 2026/07/28
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. The classical autofocusing algorithms apply a uniform search strategy, i.e., they probe multiple, uniformly distributed axial locations, which leads to heavy computational overhead. Our method substantially reduces the computational load, without sacrificing the accuracy, by skillfully selecting the next location to investigate, which results in a decreased total number of probed propagation distances. This is achieved by applying the golden selection search with parabolic interpolation, which is the gold standard for tackling single-variable optimization problems. The proposed approach is successfully applied to three diverse autofocusing cases, providing up to 136-fold speed-up.