2020/05/18 by Peter J. Christopher, Christopher, Peter J., George S. D. Gordon +3
Computer Science · Engineering · Mathematics · #Advanced Combinatorial Mathematics #Cellular Automata and Applications #FOS: Electrical engineering #FOS: Physical sciences #Image and Video Processing (eess.IV) #Optical Polarization and Ellipsometry #Optics (physics.optics) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2005.08623
openalex publication_date 2020/05/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Due to the proliferation of spatial light modulators, digital holography is finding wide-spread use in fields from augmented reality to medical imaging to additive manufacturing to lithography to optical tweezing to telecommunications. There are numerous types of SLM available with a multitude of algorithms for generating holograms. Each algorithm has limitations in terms of convergence speed, power efficiency, accuracy and data storage requirement. Here, we consider probably the most common algorithm for computer generated holography - Gerchberg-Saxton - and examine the trade-off in convergent quality, performance and efficiency. In particular, we focus on measuring and understanding the factors that control runtime and convergence.