Treffer: Performance evaluation of Python and MATLAB for CGH generation using layer-based approach.

In the field of computational holography, creating intricate holographic patterns is a fundamental yet computationally intensive endeavor, posing substantial challenges in obtaining large space-bandwidth product. The computational burden for calculating computer generated hologram (CGH) is notably affected by various factors, with object and CGH sizes being the prominent ones. As such, the task of optimizing CGH generation algorithms for larger matrix dimensions is paramount, especially in practical applications such as holographic dynamic displays. This work presents a comprehensive comparative analysis of two widely used programming languages, Python and MATLAB, for CGH calculation. The study tends to provide valuable insights to predict the suitability of these languages for CGH calculation in terms of efficiency and performance. The large matrix dimensions up to 8192 × 8192 are used as test cases to ensure the relevance and practicality of the findings. Our findings reveal that MATLAB and Python perform comparably in terms of the quality of reconstruction objects and also the execution time disparity diminishes, particularly for higher matrix dimensions. As a result, users can choose either language based on their requirement and personal comfort with the programming environment. [ABSTRACT FROM AUTHOR]

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