Quantitative phase maps denoising of long holographic sequences by using SPADEDH algorithm.

Area of Science:

• * Digital Holography
• * Image Processing
• * Computational Optics

Background:

• * Digital holography generates phase maps susceptible to noise.
• * Existing denoising methods may require noise statistics or alter phase information.
• * Accurate phase maps are crucial for quantitative analysis, especially in biological imaging.

Purpose of the Study:

• * To adapt the SPArsity DEnoising of Digital Holograms (SPADEDH) algorithm for denoising mod 2π wrapped phase maps.
• * To evaluate the performance of the adapted SPADEDH algorithm against traditional filters.
• * To demonstrate the algorithm's utility in processing experimental quantitative phase maps (QPMs) and assisting phase unwrapping.

Main Methods:

• * Adaptation of the l(1) minimization SPADEDH algorithm for phase map denoising.
• * Numerical simulations with varying parameters to quantify denoising efficiency.
• * Comparative analysis against median and Gaussian filtering techniques.
• * Experimental validation using long-sequence QPMs of in vitro cells.

Main Results:

• * The adapted SPADEDH algorithm effectively suppresses noise in wrapped phase maps.
• * Performance was quantified and compared favorably against median and Gaussian filters.
• * Demonstrated successful application to experimental in vitro cell QPMs, yielding high-quality results.
• * Showcased the algorithm's capability to assist local phase unwrapping.

Conclusions:

• * The adapted SPADEDH algorithm offers a robust and efficient method for denoising digital holography phase maps.
• * It provides superior noise reduction without prior noise statistics knowledge.
• * The method enhances the quality of QPMs for biological applications and supports subsequent phase unwrapping processes.