Accurate subpixel shifting of point spread functions.

Area of Science:

• Optical imaging
• Computational microscopy
• Image processing

Background:

• Accurate emitter localization relies on precise subpixel shifting of point spread function (PSF) models.
• Camera-recorded PSFs deviate from true system PSFs due to pixel integration, introducing systematic biases in localization.
• Existing methods struggle with pixel integration errors, impacting registration accuracy.

Purpose of the Study:

• To develop novel filter kernels for accurate subpixel shifting of images.
• To mitigate systematic biases caused by pixel integration in PSF modeling.
• To improve the precision of emitter localization in imaging systems.

Main Methods:

• Proposed a set of filter kernels designed for arbitrary subpixel image shifting.
• Each filter kernel pixel is defined by a 2D polynomial function of shift values.
• Convolved the proposed filters with images to achieve precise subpixel shifts.

Main Results:

• The developed filter kernels accurately shifted images by arbitrary subpixel amounts.
• Tested filters on three distinct PSFs, demonstrating significant error reduction.
• Achieved error reductions exceeding a factor of 20 compared to PSF models evaluated at pixel centers.

Conclusions:

• The proposed filter kernels effectively address errors from pixel integration in PSF modeling.
• This method offers a substantial improvement in subpixel shifting accuracy for emitter localization.
• The filters provide a robust solution for enhancing registration and localization precision.