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Practical Camera Sensor Spectral Response and Uncertainty Estimation.

Mikko E Toivonen¹, Arto Klami¹

¹Department of Computer Science, University of Helsinki, 00560 Helsinki, Finland.

Journal of Imaging

|August 30, 2021

Summary

This summary is machine-generated.

This study introduces a practical method to accurately estimate camera sensor spectral response and its uncertainty using just 15 images. This technique is broadly applicable to various camera sensors for improved computer vision applications.

Keywords:

calibration data fusion spectral response stochastic optimization uncertainty estimation

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Area of Science:

Computer Vision
Image Processing
Spectroscopy

Background:

Accurate camera spectral response is crucial for tasks like illumination estimation and color correction.
Existing methods may have limitations in applicability or require extensive data.

Purpose of the Study:

To develop a practical and broadly applicable method for estimating camera sensor spectral response and uncertainty.
To provide high-resolution spectral response estimates with low errors.

Main Methods:

A novel imaging method combined with a flexible algorithm.
Utilizes a small dataset of 15 images (diffraction and color patches with known spectra).
Employs an ensemble of response estimation models for uncertainty quantification.

Main Results:

Achieved high-resolution spectral response estimates with low errors.
Uncertainty estimates were successfully obtained through model ensembling.
The method demonstrated consistency with previously reported spectral response estimates.

Conclusions:

The presented method offers a practical solution for camera spectral response estimation.
Its applicability extends to any camera sensor within the visible spectrum.
The technique provides reliable estimates crucial for advanced computer vision tasks.