Back-of-the-envelope image resolution estimation using an aberrated Rayleigh criterion

Area of Science:

• Optical Engineering
• Image Sensor Technology
• Metrology

Background:

• Image quality in optical imaging sensors is paramount, directly correlating with sensor performance.
• Key factors influencing image quality include the point-spread function (PSF), sampling, and signal-to-noise ratio.
• Sensor resolution is critically dependent on the PSF, which is often degraded from the diffraction limit by optical aberrations and pixel size.

Purpose of the Study:

• To develop simplified, back-of-the-envelope calculations for estimating the PSF size of non-diffraction-limited imaging sensors.
• To provide a method for allocating blur contributions from various sources (e.g., wavefront errors) during sensor design.
• To enable better prediction and control of image quality based on required sensor resolution.

Main Methods:

• Development of two distinct, simplified calculation methods for estimating non-diffraction-limited PSF size.
• Utilizing sensor-level required resolution as the primary input for the PSF size estimation.
• Establishing a framework for allocating blur budgets to specific optical and sensor parameters.

Main Results:

• Successful derivation of two practical calculation methods for estimating imaging sensor PSF size.
• Demonstrated that these estimates can guide the allocation of blur contributions during the sensor design process.
• Provided a quantitative approach to manage trade-offs between resolution and various blur sources.

Conclusions:

• The developed calculations offer a valuable tool for optical imaging sensor design and performance prediction.
• Effective PSF size estimation facilitates the management of blur budgets, leading to optimized image quality.
• This approach aids engineers in addressing non-diffraction-limited scenarios by systematically allocating design parameters.