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Image quality evaluation and tolerance analysis method for optical-digital imaging systems.

Junming Chen, Xianglong Mao, Boyu Mao

|March 18, 2026

Summary

This summary is machine-generated.

This study introduces a new, dataset-independent metric for optical-digital joint optimization, improving image quality evaluation. This metric enables accurate tolerance analysis and error budget allocation for enhanced optical-digital imaging systems.

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Area of Science:

Optics and Image Processing
Computational Imaging

Background:

Optical-digital joint optimization integrates optical systems with image processing for improved performance.
Current methods rely on dataset-dependent similarity metrics, limiting objective performance evaluation.
Existing metrics fail to objectively characterize optical-digital imaging system performance.

Purpose of the Study:

To propose a novel, dataset-independent image quality evaluation metric for optical-digital systems.
To develop a tolerance analysis method for optical-digital imaging systems.
To introduce an image-plane compensation algorithm for non-ideal systems.

Main Methods:

Developed a metric based on a normalized spatial-frequency contrast sensitivity function (CSF)-weighted modulation transfer function (MTF).
Employed Monte Carlo simulations for tolerance analysis, evaluating individual and combined effects of tolerances.
Introduced an image-plane compensation algorithm to correct aberrations.

Main Results:

The proposed metric objectively reflects system performance, independent of specific datasets.
Tolerance analysis allows for precise error budget allocation to different system components.
The compensation algorithm effectively corrects aberrations in non-ideal imaging systems.

Conclusions:

The novel metric and tolerance analysis method support practical engineering implementation of optical-digital joint optimization.
The developed techniques enhance the robustness and performance of optical-digital imaging systems.
This work provides a framework for more reliable and efficient design of advanced imaging systems.