Speckle denoising by variant nonlocal means methods

Area of Science:

• Optics and Imaging Science
• Image Processing and Signal Analysis

Background:

• Digital coherent imaging systems, like digital speckle pattern interferometry, suffer from speckle noise degrading image quality.
• Speckle noise, arising from the coherent light source, limits the application scope of these advanced imaging systems.

Purpose of the Study:

• To evaluate the performance of Nonlocal Means (NLM) and its variants for speckle noise reduction.
• To compare NLM-based methods with existing speckle denoising techniques for amplitude and phase images.

Main Methods:

• Utilizing NLM-shaped adaptive patches and NLM-reprojection schemes for denoising.
• Quantifying performance using Peak-to-Signal Noise Ratio (PSNR) and Image Quality Index (IQI).

Main Results:

• NLM and variant methods demonstrate significant improvements in intensity and phase images.
• These denoising techniques show superior performance compared to other existing speckle reduction methods.

Conclusions:

• NLM-based denoising methods are highly effective and feasible for speckle noise reduction.
• The study confirms the ability of NLM variants to favorably enhance image quality in digital coherent imaging.