Edge sparsity criterion for robust holographic autofocusing.

Area of Science:

• Digital Holographic Imaging
• Optical Microscopy
• Image Processing

Background:

• Autofocusing is critical for digital holographic imaging.
• Existing autofocusing methods struggle with connected objects of varying optical properties.
• Polarity shifts in older autofocusing criteria complicate sample-specific adjustments.

Purpose of the Study:

• To develop a robust and accurate autofocusing criterion for digital holographic imaging.
• To address the limitations of previous autofocusing methods, particularly with complex samples.
• To introduce a novel criterion based on wavefront edge sparsity.

Main Methods:

• Proposed a new autofocusing criterion termed "sparsity of the gradient" (SoG).
• SoG leverages the edge sparsity of the complex optical wavefront.
• Validated the method across diverse imaging scenarios.

Main Results:

• Demonstrated successful autofocusing using the SoG criterion.
• Applied SoG to a wide range of objects, including resolution targets and various biological smears.
• Achieved accurate focusing for stained and unstained Papanicolaou smears, tissue sections, and blood smears.

Conclusions:

• The sparsity of the gradient (SoG) is a robust and accurate autofocusing criterion.
• SoG overcomes challenges faced by previous autofocusing methods in digital holographic imaging.
• The proposed method shows broad applicability for imaging diverse microscopic samples.